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Trends and Emerging Narratives, 2020
The Kenyan
Social Media Landscape:
B.Sc. Global Leadership and Governance
M.Sc. Information Security
The Kenyan Social
Media Landscape:
Trends and Emerging
Narratives, 2020
Cover image: © mimagephotography
Paul Watzlavick
The Counselor for Public Affairs,
U.S. Embassy, Nairobi
“The United States
is proud to support
SIMELab and their
groundbreaking
research into
Kenyan social
media.The future
is digital, so that’s
where we need
to be: generating
innovative solutions
to global challenges
together.”
International Symposium on Social Media
USIU-Africa, Nairobi / September 11-12, 2019
“Use of digital media and social media are connected
to deep-rooting changes of citizens’ self-concepts”
Prof. Dr. Martin Emmer (FU Berlin)
(From Left to Right)
Dr. Geoffrey Sikolia,
Mr. Robert Alai, Ms. Juliet
Kanjukia, Ms. Ivy Mungai
and Mr. Dennis Itumbi in a
panel discussion on “Social
Media and Governance”
during the 2019 International
Symposium on Social Media
(From Left to Right)
Mr. Alex Taremwa,
Ms. Noella Musundi,
Mr. David Gitari, Ms. Lucy
Wamuyu and Martin Muli
in a panel discussion on
“Social Media versus
Mainstream Media”
during the 2019 International
Symposium
In this report
Foreword ........................................................................................................................................................... 10
Acknowledgements ..................................................................................................................................12
Key Discoveries in 2020 ...........................................................................................................................14
Survey Sypnosis ............................................................................................................................................16
1. Social Media Consumption among Kenyans ...............................................18
1.1. Social Media Use Among Kenyans in 2020 .....................................................18
1.2. Trends and Emerging Narratives, 2020 .............................................................19
1.3. Use of Social Media by Age .........................................................................................19
1.4. Use of Social Media by Gender ................................................................................20
1.5. Use of Social Media by Geolocation ....................................................................21
1.6. Use of Social Media by Level of Education .....................................................21
1.7. Use of Social Media by Income Levels in Nairobi ........................................22
2. Issues Of Focus In The Use Of Social Media ................................................. 23
3. Frequency Of Accessing Social Media ...........................................................24
4. Devices Used To Access Social Media ............................................................25
5. Physical Location Of Accessing Social Media .............................................26
6. Accessing Social Media Using Web Browsers or Mobile Apps ..............27
7. Daily Time Spent On Social Media ...................................................................28
8. Following Brands Online ....................................................................................30
9. Time Of Day When Kenyans Access Social Media ....................................30
10. Online Harassment ...............................................................................................31
10.1. Online Harassment – Less Severe Forms ..........................................................31
10.2. Online Harassment – Severe Forms .....................................................................33
11. Use Of Pseudonyms ..............................................................................................34
12. Motivations For Using Social Media ................................................................35
13. Motivations For Using Specific Social Media ...............................................36
14. Reading of Online Blogs Among Kenyans ...................................................37
14.1. Reading of Online Blogs by Gender .....................................................................38
14.2. Reading of Online Blogs by Geolocation ..........................................................38
14.3. Reading of Online Blogs by Income Levels in Nairobi .............................39
14.4. Frequency of Reading Online Blogs ....................................................................40
15. Online Discussions and Debates ......................................................................40
16. Online Misinformation, Disinformation and Fake News .........................42
16.1. False, Incorrect or Inaccurate Information ......................................................42
16.2. Information That Is Biased or Meant To Mislead Deliberately ............43
16.3. Fake News ..............................................................................................................................44
16.4. Negative News ....................................................................................................................44
17. Social Media DataMining and Analytics .......................................................48
17.1. A Social Network Analysis of The #KomeshaCorona Hashtag ...........48
18. Commentaries ........................................................................................................55
18.1. Misinformation and COVID-19 ..................................................................................56
18.2. Influencer Marketing and Consumer Behavior Post-COVID-19 ........57
18.3. Social Media as a Cause of Hate speech? .........................................................59
18.4. Social Media In The New Decade ...........................................................................60
18.5. Harnessing Social Media Consumption in Fighting the
COVID-19 Pandemic Among the Youth .............................................................62
18.6. Dealing with Pandemic Stigma: Social Media Usage During
COVID-19 in Kenya ............................................................................................................63
18.7. Social Media Fake News in Times of the COVID-19 Pandemic ...........64
18.8. Trends in Social Media Marketing .......................................................................66
18.9. Social Media Addiction .................................................................................................. 68
18.10. A Pandemic Conundrum: Social Media and Misinformation .............70
18.11. The Battle in Understanding Consumer Audiences .................................70
18.12. Anonymity and Social Media ..................................................................................... 72
18.13. Social Listening - What Can Brands Learn From Online
Conversations? ....................................................................................................................73
SIMELab Team...............................................................................................................................................75
References .......................................................................................................................................................77
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
8
About SIMElab Africa
SIMElab Africa (Social Media Lab Af rica) is an interdisciplinary Center
for research in Big Data and Social Media Analytics Research Lab
housed at USIU-Africa’s Freida Brown Innovation Center. SIMElab
Africa offers a research and development environment to USIU-
Africa faculty and students, civil society and corporate businesses,
and policymakers in Kenya and beyond. SIMELab is jointly funded by
USA Embassy in Nairobi and USIU-Africa.
The Objectives of the SIMElab are to:
• Provide an annual status on social media consumption in Kenya
leading to an annual report;
• Conduct quarterly trainings on social media analytics to
academics and private sector in Kenya;
• Develop a monthly data repository on social media consumption
in Kenya; and
• Disseminate quality and reputable research through journal and
conference publications.
Disclaimer
The views and opinions expressed in this report are those of the authors and do not necessarily reflect official
position of any specific organization or government.
For more information, contact
SIMElab Africa,
simelabadmin@usiu.ac.ke | +254 730 116 821
Copyright © SIMElab Africa, 2020; All Rights Reserved
Citation
Wamuyu, P. K. (2020). The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020, SIMElab, Nairobi.
https://www.usiu.ac.ke/assets/file/SIMElab_The_Kenyan_Social_Media_Landscape_report.pdf
Ibrahim Hassan Hudle
A data collection assistant
in Garissa County, taken
during data gathering on
March 18, 2020
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
10
F
Welcome to the 2nd
Edition of the Social
Media Consumption
in Kenya Report. Social
media sites and apps
have become the new
home where Kenyan
families, friends,
influencers, brands, and bloggers converge
multiple times daily to share updates and
communicate. This year, we highlight trends
on social media use in Kenyans’ daily lives as
well as newly emerging narratives on online
misinformation, disinformation, and fake news,
cyber harassment, social media use during the
Coronavirus pandemic, Social Media Big Data
Mining and the challenges with social media.
Social media usage patterns have
changed over the last one year, with
Facebook users having decreased by
6.8%, while the number of Snapchat
users increased by 17.3% and Twitter
users increasing by 13.4%. The surge
in the use of IMO, Likee, Vskit,
Telegram, and Vimeo as social
media channels among Kenyans
shows a change in social media
users’ priorities and interests among
different demographic groups as
people seek for ways to quickly check
news and spread useful information.
Fake and negative news, false,
incorrect, and inaccurate information
and information that is biased or
meant to mislead deliberately have
become common on social media and
many Kenyans are likely to share the
same intentionally or unintentionally.
Online harassment is also common
and takes on many incarnations on
social media with the aim of causing
emotional distress to real or imaginary
foes. Even though most Kenyans
access social media using mobile
apps, privacy concerns have made
a good percentage of users access
social media using mobile browsers
which are presumed to offer more
privacy features than standalone
mobile apps.
Even though the cost of internet in
Kenya is considered to be among the
cheapest in Africa, the average cost
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
11
of access has remained relatively high,
making social media access generally
unaffordable to many Kenyans. This could
be the reason why 54.3% of the people
living in urban areas access social media
from the f ree public hotspots, while 46.1%
of the people living in rural areas access
social media from the cyber cafés and
most of the people more than 25 years old
access social media from offices.
Kenya has a robust blogger community
with hundreds of active bloggers and a
variety of stimulating blogs on politics,
agriculture, technology, education,
fashion, food, entertainment, sports, and
travel. Online discussions and public
debates using social media and apps have
also become part of the daily life of many
Kenyans. Online social media debates
among Kenyans are known to influence
individual attitudes and behaviors in
relationships, politics, fashion, and how
audiences engage with brands.
On opportunities and challenges with
social media, we have reviews and research
articles on anonymity and self-disclosure,
social media addiction, hate speech, and
a journey to the future of social media
sites and apps. We also have an article on
social media big data mining on Twitter.
Organizations are trawling social media
sites in search of information they can use
for purposes of proper decision making.
This is “Social Media mining”, the
process of representing, analyzing, and
extracting actionable patterns from
social media data to draw conclusions
about the populations of the users.
Patrick Kanyi Wamuyu, Ph.D.
SIMElab Coordinator
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
12
Design, Layout and Production
Tonn Kriation
A
In developing the Kenya Social Media Consumption Report 2020, SIMElab
received invaluable collaboration and input from key partners as listed below.
Data Collection Assistants
We would like to single these individuals who worked tirelessly during
data collection phase of the project
Mr. Anthony Kiingati
Ms. Diana Meso
Mr. David Lomoywara
Mr. Ernest Mwanzi
Ms. Faith Mudanya
Mr. Ibrahim Hassan Hudle
Ms. Irene Ogutu
Ms. Immaculate Tallam
Mr. Jacktone Momanyi
Dr. James Karimi
Mr. James Monchoi
Ms. Maribor Liza Orre
Mr. Martin Wagura
Dr. Quin Awour
Ms. Risper Ndirangu
Ms. Susan Muchai
Commentaries
Ms. Ashleigh Jacobs
Mr. Augustine Kihiko
Mr. Brian Kisuke
Mr. David Lomoywara
Mr. Ernest Mwanzi
Dr. Geoffrey Sikolia
Ms. Immaculate Tallam
Mr. Japheth Mursi
Mr. Kelvin Jonck
Ms. Kristina Sutton
Prof. Dr. Martin Emmer
Prof. Melissa Tully
Technical Support
Ms. Brenda Odhiambo
Dr. Gabriel Okello
Mr. Lawrence Okayo
Ms. Taigu Muchiri
The U.S.A Marafiki, Kenya jointly with USIU-Africa provided the funding to setup the
SIMElab Africa at USIU-Africa in 2018 and has continued to financially support the
activities of the SIMElab.
NRF/1/MMC/418
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
14
43%
17.7%
83.5%
6.8%
decrease in number of
Facebook users among
Kenyans
in favor of
67% 63%
61%
Kenyan youth
have abandoned
Facebook
of LinkedIn users
only access it for
less than thirty
minutes daily.
78%
follow and interact with
brands on social media
33%
have experienced
online harassment
Kenyans who have come
across fake news and are
likely to have shared it
Snapchat users
have increased
Twitter users
have increased
by
by
54.3%46.1%
people living in
urban areas access
social media from
public hotspots
people living in
rural areas access
social media from
cyber cafés
while
23.3%
prefer to access social media
through their mobile browsers
rather than using mobile apps
61%
Kenyan men use
pseudonyms on
Twitter
47.7%
use fictitious names when
accessing social media
86.9%
read online blogs
14.3%
KENYANS HAVE LEARNED TO RELY
ON SOCIAL MEDIA REVIEWS AND
BLOGS TO MAKE THEIR DECISIONS
K D 2020
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
15
43%
17.7%
83.5%
6.8%
decrease in number of
Facebook users among
Kenyans
in favor of
67% 63%
61%
Kenyan youth
have abandoned
Facebook
of LinkedIn users
only access it for
less than thirty
minutes daily.
78%
follow and interact with
brands on social media
33%
have experienced
online harassment
Kenyans who have come
across fake news and are
likely to have shared it
Snapchat users
have increased
Twitter users
have increased
by
by
54.3%46.1%
people living in
urban areas access
social media from
public hotspots
people living in
rural areas access
social media from
cyber cafés
while
23.3%
prefer to access social media
through their mobile browsers
rather than using mobile apps
61%
Kenyan men use
pseudonyms on
Twitter
47.7%
use fictitious names when
accessing social media
86.9%
read online blogs
14.3%
KENYANS HAVE LEARNED TO RELY
ON SOCIAL MEDIA REVIEWS AND
BLOGS TO MAKE THEIR DECISIONS
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
16
S S
The Kenyan Social Media Landscape:
Trends and Emerging Narratives, 2020
Over the years, social media sites and
apps have created opportunities for
people to stay connected to family
and friends and have enhanced the
possibilities of making new friends
from every corner of the world. Social
networking sites have emerged as
important communication channels
used by individual consumers to
create content, distribute materials,
share ideas, express opinions, and use
information and knowledge. With
millions of daily active users, social
media have become essential tools
for organizations as they enhance
collaboration, knowledge sharing, and
increase productivity among workers.
The use of social media has generated
a lot of market and academic research
over the years as researchers try to
synthesize acceptance, appropriation,
and adoption of social networking
sites and apps. Interactions facilitated
by social media have become an
integral part of many Kenyans’ daily
lives for telling their stories and
sharing narratives.
The report draws from a nationally
representative survey of social media
consumption patterns among
different demographic segments,
conducted between February and
March 2020. The survey sampled
10,658 respondents aged between 14
and 55 from 19 counties drawn from
Kenya’s former eight administrative
provinces – Nairobi, Coast, Central,
Western, Nyanza, Eastern, Rift Valley,
and North Eastern.
From the 9,740 sampled, 9,728
questionnaires were fully answered –
representing a health response rate
of 99.9%. To provide a comparative
analysis, a proportional number of
counties were selected form each
province. The counties with the
highest access to the Internet in each
province, as per the data released
by the Kenya National Bureau of
Statistics (2016) were selected.
The 20 counties selected were Nairobi
(Nairobi Province), Mombasa and
Taita Taveta (Coast), Meru, Embu,
Makueni, and Marsabit (Eastern),
Bungoma and Kakamega (Western),
Mandera and Garissa (North Eastern),
Trans Nzoia, Kajiado, Kericho, Turkana
and Baringo (Rift Valley), Kisumu and
Kisii (Nyanza), and Nyeri and Kirinyaga
(Central). Relatedly, the sample
size per county were as follows:
Mombasa (n=598); Taita Taveta
(n=589); Bungoma (n=596); Trans
Nzoia (n=586); Nyeri (n=642); Turkana
(n=362); Kisumu (n=505); Kirinyaga
(n=656); Embu (n=575); Garissa
(n=393); Kajiado (n=559); Kakamega
(n=550); Kericho (n=580); Kisii (n=589);
Makueni (n=598); Marsabit (n=304)
and Nairobi (n=1,058). Due to COVID-19
lockdown and national wide curfew, it
was not possible to collect data in the
counties of Baringo, Mandera, and
Meru in time for report preparation.
However, data was later collected in
Mandera (n=499), and Meru (n=419).
From the selected counties, one
urban and one rural location with
Internet penetration (as per KNBS
2016) report were selected for data
collection. The locations selected for
data collection except Nairobi were
as follows: Mombasa (Mombasa
Town and Changamwe); Taita
10 658
19
respondents
aged between 14 & 55yrs
counties
‘‘The use of
social media
has generated
a lot of market
and academic
research over
the years as
researchers try
to synthesize
acceptance,
appropriation,
and adoption
of social
networking sites
and apps.’’
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
17
Taveta (Mwatate and Wundanyi);
Bungoma (Bungoma Town and
Kanduyi); Trans Nzoia (Kitale Town
and Kiminini); Nyeri (Nyeri Town
and Naro Moru); Turkana (Lodwar);
Kisumu (Kisumu City and Nyando);
Kirinyaga (Kerugoya, Sagana,
and Kagio); Embu (Embu Town
and Siakago); Garissa (Garissa
town and Balambala); Kajiado
(Kajiado Town and Loitokitok);
Kakamega (Kakamega Town and
Shinyalu); Kericho (Kericho Town
and Londiani); Kisii (Kisii Town and
Nyamache); Makueni (Wote and
Kibwezi); and Marsabit (Marsabit
Town and Laisamis). However,
since there is no distinction
between urban and rural areas in
Nairobi, the capital city was sub-
divided according to the socio-
economic demographics used by
the KNBS as follows: lower income,
middle income, and high income.
Specifically, for lower-income, the
data were collected in (Mathare,
Kangemi, Kawangware, Mukuru
Kwa Njenga, Mukuru Kwa Reuben,
Laini Saba, Korogocho, Kariobangi,
Dandora, Kayole, and Kiamaiko.
For middle-income, the data were
collected in Parklands, Highridge,
Mountain View, Lang’ata, South
C, Nyayo Highrise, Nairobi West,
Woodley, Westlands. Umoja,
Imara Daima, Savannah, and
Eastleigh and Westlands. Runda,
Kitisuru, Kileleshwa, Muthaiga,
Karen, and Kilimani represented
high-income neighborhoods.
Map 1:
Data colletion sites
Makueni
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
18
1 S M C K
Currently, there are many social media sites and apps dedicated to social
networking. In today’s digital age, most relationships are often begun and
developedon social media sites and apps. Social media users create a public
or semi-public profile and connect with other users within a bounded system.
Social media sites and apps is the new home where families, friends, influencers,
brands and bloggers converge multiple times daily to share updates and
communicate.
11 S M K 2020
Outside the corporate world, few people had used Microsoft Teams or Zoom in
Kenya. However, with COVID-19 pandemic, these video conferencing and web
conferencing platforms are now common vocabulary among ordinary citizens.
Similarly, we find new types of social media being accessed locally that did not
have much following before including TikTok, IMO, Likee, Vskit, Telegram and
Vimeo. In terms of the most used social media among Kenyans, just as it was
last year, WhatsApp (89%), Facebook (81.7%) and YouTube (51.6%), are still the
top three most used social media. However, while the number of WhatsApp
users have increased marginally in 2020, the number of Facebook users have
decreased by 6.8%. Worth mentioning are the new entrants to the top ten most
used social media in Kenya which now include TikTok (8.8%), Telegram (15.5%)
and Facebook Messenger (37.4%). The other mostly used social networking sites
and apps are shown in Figure 1. Twitter and Snapchat users have increased by
6.3%, and 4.4% respectively in 2020.
89%
81.7%
58.4%
Most used social media apps
Figure 1:
Use
of Social
Media in Ke
nya 89%
81.7%
58.4%
37.4%
37.3%
34.4%
15.5%
13.5%
9.1%
8.8%
8.6%
6.0%
2.2%
WhatsApp
Facebook
YouTube
Facebook
Messenger
Instagram
Twitter
Telegram
Snapchat
Linkedln
TikTok
Skype
Pinterest
Vimeo
Facebook users
have decreased by
6.8% in 2020
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
19
12 T E N, 2020
With the uptake in visual content consumed from social media
becoming highly popular, there is a surge in penetration and acceptance
of other less commonly known social media sites and apps in Kenya.
Figure 2 shows a comparison in the number of early users of these social
networking sites and apps among the survey respondents.
Figure 2:
Social Media social net
working
si
tes and apps gaining in
popularity among Ke
nyans
69%
15%
6%
6%
4%
Google Duo
WeChat
Vskit
Likee
IMO
13 U S M A
Could it be that the youth in Kenya are beginning to abandon Facebook
in favor of Snapchat, TikTok, and Instagram? From Figure 3 on the next
page, Snapchat, TikTok, and Pinterest are much more likely to be used
by users who are 14-20 years old, while the social media users who are 21-
25 years old use Instagram, Snapchat, and Telegram. Social media users
who are 26-35 years old are more active on the professional network
LinkedIn, Skype, and Twitter. This is the age group where many people
seek to establish their careers. 36-45 year-olds mostly use Facebook and
WhatsApp, 26-35-year olds use LinkedIn and Skype while those 45 years
and above use WhatsApp and Skype. Instagram and Snapchat are the
social media social networking sites and apps of choice for most of the
21-25 year-olds, who are the most active age group on social media in
2020, unlike in 2019 where the most active age group was 26-35 years old.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
20
14 U S M G
Kenyan men are more active in social media. As shown in Figure 4, men
frequently use Telegram (66.1%), LinkedIn (62.1%), and Skype (61.6%). The women
in Kenya are most active on Snapchat (61.9%), TikTok (53.6%) and Pinterest (50%).
0.0
5.0
10.0
15.0
20.0
25.0
percentages
years
30.0
35.0
40.0
45.0
50.0
14 - 20 21 - 25 26 - 35 36 - 45 A bo v e 45
Facebook
Twitter
WhatsApp
Instagram
Snapchat
YouTube
Linkedln
TikTok
Vimeo
Pinterest
Telegram
Skype
Facebook
Messenger
13.1
11.4
13.315.5
14.5
8.5 13.2 20.8
16.4
13.4
9.6
39.2
40.3
37.8 45.1
44.7
41.0
35.4 41.2
42.4
43.0
39.7 44.5
33.5
30.4
32.8
29.8
28.8
24 29.7 39.2
31.3
24.8 30.0
30.2
30.0 38.5
13.1
11.6
13.0
8.2
6.7 11.2
12.3
11.3
8.6
7.29.0
9.3 13.0
4.2
3.8 6.1
2.4
2.3
3.7
4.6
3.0
3.4
3.4
1.7
2.9 5.4
19.4
22.3
26-35 yrs old are more
active on the
professional networks
LinkedIn, Skype, and
Twitter
Figure 3:
Use
of Social Media by Age
This is the age group
where many people
seek to establish
their careers
0.0
10.0
20.0
percentages
30.0
40.0
50.0
60.0
70.0
Female Male
Figure 4:
Use
of Social Media by Gender
Facebook
Twitter
WhatsApp
Instagram
Snapchat
YouTube
Linkedln
TikTok
Vimeo
Pinterest
Telegram
Skype
Facebook
Messenger
44.6
40.4
45.4
44.8
61.9
43.2
38.4
43.8
53.6
39.5
50.0
33.8
37.8
55.3
59.5
54.5
55.1
37.9
56.8
61.6
56.2
46.4
60.5
50.0
66.1
62.1
women are
most active
on Snapchat
61.9%
men are
most active
on Telegram
66.1%
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
21
15 U S M G
A majority of Kenyans in the rural areas use Facebook Messenger (45.3%),
Facebook (44.5%) and WhatsApp (44.2%), compared to a majority of
urban residents who use TikTok (67.9%), Vimeo (67.4%), and Pinterest
(63.4%), as shown in Figure 5 below. There are several technological
infrastructures challenges in the rural areas which prevent the use of
high resource-demanding social media sites and apps. WhatsApp, and
YouTube in rural areas could be attributed to being complementary
services offered by the telecommunications service providers.
0.0
10.0
20.0
percentages
30.0
40.0
50.0
60.0
70.0
Urban Rural
Facebook
Twitter
WhatsApp
Instagram
Snapchat
YouTube
Linkedln
TikTok
Vimeo
Pinterest
Telegram
Skype
Facebook
Messenger
55.5
60.5
55.8
58.9
62.9
57.6
61.9
54.7
67.9
67.4
63.4
60.2
59.6
44.5
39.5
44.2
41.1
37.1
42.4
38.1
45.3
32.1
32.6
36.6
39.8
40.4
67.9%of urban
residents use TikTok
while 45.3% of
rural residents use
Facebook Messenger
Figure 5:
Use
of Social Media by Geolocation
16 U S M L E
From Figure 6 on the next page, the use of Facebook is more common
among those with primary school and high school levels of education.
Among those with a higher education level (undergraduate and
graduate), the most common social media platform is LinkedIn.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
22
In the primary school category, the preferred social media channels are Facebook,
WhatsApp, and Vimeo. For high school graduates, the most dominant platform
is Facebook (27.5%) followed by WhatsApp (26.7%) and YouTube with (24.1%).
However, among those with college-level education, Facebook Messenger is the
most preferred (40.8%). The second most popular social media platform among
those with college-level education is Telegram (38.6%) followed by YouTube
(38.3%). For the undergraduate category, the leading social media platform in
use is LinkedIn (41.4%) followed by Pinterest (40.7%). Skype is the most used social
media among those with masters and doctorate level degrees (14.9%) followed
by LinkedIn (12.6%) and Twitter (9.5%). Overall, there is heavy use of social media
among those with college-level education, while the least usage of social media
is among the primary school graduates.
17 U S M N
In Nairobi, the majority of residents, by population, live in urban slums. Thus,
those who live in informal settlements or the low-income residential areas use
Facebook (33.9%), WhatsApp (24.1%), and Vimeo (19.2%) as their social media
platforms of choice as indicated in Figure 7. The middle-income residents of
Nairobi mostly use Telegram (48.6%), Skype (48.4%), and TikTok (45.0%). High-
income Nairobi residents mostly use LinkedIn (55.2%), Vimeo (53.8%), and
Snapchat (50.8%).
0.0
5.0
10.0
15.0
20.0
25.0
percentages
30.0
35.0
40.0
45.0
Primary
School
High
School
College
Graduate
Undergraduate Postgraduate
Facebook
Twitter
WhatsApp
Instagram
Snapchat
YouTube
Linkedln
TikTok
Vimeo
Pinterest
Telegram
Skype
Facebook
Messenger
7.0
3.6 6.8
4.1
4.4
4.9
2.7 4.5
5.6
6.3
3.3
3.0
3.3
27.5
19.6 26.7
21.0
22.7
24.1
12.8 22.8
21.5
16.9
15.8 19.0
14.2
37.3
37.0
37.4
37.3
35.0 38.3
30.5
38.2
38.2
31.7 38.6
35.0
22.1 30.4
22.7 30.0
30.4
25.7 41.4
24.9
25.9 31.4 40.7
31.5
32.5
6.2 9.5
6.4
7.6
7.5
7.0 12.6
7.08.7
7.28.5
7.9 17.9
40.8
Figure 6:
Use
of Social Media by Education 41.4% of
undergraduates
use LinkedIn
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
23
2 I
Most Kenyans are using social media for social issues, entertainment,
education, jobs, politics, sports, religion, and environment and climate
matter as shown in Figure 8. Facebook (64%), WhatsApp (80%), Facebook
Messenger (30%), and Telegram (9.4%) are mostly used for social issues,
while Instagram (27%), Snapchat (11%), YouTube (56%), TikTok (8%), Vimeo
(1.4%), and Pinterest (4.2%) are frequently used for entertainment.
LinkedIn (14%) and Skype (7%) are mostly used for job-related issues
while Twitter (35%) is generally used for politics.
0.0
10.0
20.0
percentages
30.0
40.0
50.0
60.0
Low Middle High
Facebook
Twitter
WhatsApp
Instagram
Snapchat
YouTube
Linkedln
TikTok
Vimeo
Pinterest
Telegram
Skype
Facebook
Messenger
33.9
15.6
24.1
14.9
12.4
16.5
4.7
11.5
8.8
19.2
10.3
7.2
11.3
33.9
39.3
39.4
44.1
36.8
42.3
40.1
43.8
45.0
41.1
26.9
48.6
48.4
32.3
44.8
36.4
41.0
50.8
41.2
55.2
44.7
46.3
53.8
48.6
44.2
40.3
33.9% of
low-income
residents
use Facebook
Figure 7:
Use
of Social Media by income levels in Nairobi
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
24
3 F A S M
Most of the social media users in Kenya access more than one site and application
daily, as indicated in Figure 9. The data on social media use shows that 91% of
WhatsApp users access the channel daily, with 8% accessing it weekly, while 1%
use it less often. 77% of Facebook users visit the site daily, 19% use the platform
weekly, while 4% say they visit the site less often. 67% of YouTube users visit the
site daily, another 28% say they use it a few days a week, while 6% say they use
the video-sharing platform less often.More than two thirds (66%) of Snapchat
users are on the platform daily, with 28% who say they check in weekly, while
6% visit Snapchat less often than that. 68% of Twitter users visit the site daily,
another 26% say they visit a few days a week, while 6% say they check Twitter less
often.Some 67% of Instagram users visit the site every day, another 26% say they
use it a few days a week, while 6% say they use it less often.
Figure 8:
Issues
of Focus in the use of social media
Facebook
Twitter
WhatsApp
Instagram
Snapchat
YouTube
Linkedln
TikTok
Vimeo
Pinterest
Telegram
Skype
0.0
10.0
20.0
percentages
30.0
40.0
50.0
60.0
70.0
80.0
Education
Environment &
Climate
Entertainment Social Work
Religion Sports
Politics
Top 3 Social media apps mostly
used for entertainment are
Facebook
Messenger
59%56%47%
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
25
Compared to the 2019 data, the number of Facebook daily users has
decreased by 3.7% while the number of Snapchat users has increased
by 17.3%, Twitter users have increased by 13.4% and Instagram users have
increased by 7.2%.
4 D S M
80% of the respondents stated that they accessed social media using
mobile phones as compared to 78.6% in 2019, as indicated in Figure 10.
However, the number of WhatsApp users who use social networking
apps on mobile phones have decreased from 97.5% in 2019 to 90% in
2020 as many users access WhatsApp social networking site f rom their
offices, increasing the number of desktop (3%) and laptop (7%) users.
Similarly, the number of Facebook users accessing the platform using
mobile phones has decreased from 96.2% to 81% while those accessing
Facebook using a desktop (7%) and laptop (13%) have increased. Skype,
LinkedIn, Vimeo, YouTube, and Twitter also have a higher number of
users who access the social networking sites or apps using laptops and
desktops, with Skype at 49%, LinkedIn at 38%, Vimeo at 38%, YouTube at
29% and Twitter at (24%).
Figure 9:
Frequency
of Accessing Social Media
0.0
10.0
20.0
30.0
40.0
50.0
percentages
60.0
70.0
80.0
90.0
100.0
Daily Weekly Less Often
Facebook
Twitter
WhatsApp
Instagram
Snapchat
YouTube
Linkedln
TikTok
Vimeo
Pinterest
Telegram
Skype
Facebook
Messenger
77
91
68
67
66
67
49
73
60
57
47
55
45
19
26
8
26
27
28
35
22
29
36
20
29
28
4
6
1
6
8
6
16
5
11
23
17
15
27
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
26
5 P L A S M
People access social media from different physical locations, including their
homes (86.1%), public hotspots (29.2%), offices (22.6%), and cyber cafés (13.4%) as
shown in Figure 11. Compared to 2019, the number of social media users who
access the sites using public hotspots increased significantly in 2020 by 5.9%
while the number of users who access the sites from cyber cafés decreased
marginally by 1.1%. A majority of rural people (46.1%) still access social media
using cyber cafés, while a majority of the people (61%) living in urban areas access
social media from their offices. 44.9% of middle-income Nairobi residents and
45.1% of the high-income residents access social media in the offices, with 41.6%
of the low-income population accessing social media in cyber cafés.
Figure 10:
D
evices used to access Social Media
0.0
10.0
20.0
30.0
40.0
50.0
percentages
60.0
70.0
80.0
90.0
100.0
Laptop Desktop Mobile Phone
Facebook
Twitter
WhatsApp
Instagram
Snapchat
YouTube
Linkedln
TikTok
Vimeo
Pinterest
Telegram
Skype
Facebook
Messenger
13
16
7
12
8
21
27
11
11
26
21
15
38
7
8
3
4
4
8
11
4
5
12
8
6
11
81
77
90
84
87
71
62
85
83
62
72
79
51
percentages
Home
Public free Wi-Fi
Office
Cyber Café
Figure 11:
P
hysical Location of Accessing Social Media
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
13.4%
22.6%
29.2%
86.1%
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
27
As shown in Figure 12, 45.1% of the young people aged 21-25 years old
access social media from public hotspots while most of the people aged
more than 25 years access social media from offices.
Figure 12:
Physical Location of Accessing Social Media by age
0.0
5.0
10.0
15.0
20.0
25.0
percentages
30.0
35.0
40.0
45.0
14 - 20 21 - 25 26 - 35 36 - 45 Above 45
Years
Cyber Café
Home
Office
Public Free
Wi-Fi
10.6
13.4
4.9
14.3
36.3
36.6
27.8
45.1
31.8
30.0
39.1
26.5
15.4
13.5
18.8
10.1
5.8
6.4
9.4
4.0
Web Browser
Mobile Apps
Figure 13:
A
ccessing Social Media using Web browser or Mobile App
23.3%
95.9%
6 A S M W
M A
As Kenyans become more aware of their online privacy, they are now
choosing their mobile browsers to access social media over mobile apps.
Those using a mobile browser to access social media indicated that the
mobile browsers offer more privacy as compared to mobile apps that
access personal data on users’ location, contact lists and messages,
and require permissions to access specified content in a user’s phone
to fulfill their functionalities. However, this is how mobile apps are built
and monetized. 39.6% of women and 60.3% of men access their mobile
networking sites using mobile browsers.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
28
From Figure 15, 30% of WhatsApp users, 21% of YouTube users and 20% of Vimeo
users spend more than 3 hours online daily on these social networking sites and
apps, while 60% of WhatsApp users, 46% of Facebook users and 29% of YouTube
users spend more than 2 hours online everyday as shown in figure 15. Quite
surprisingly, LinkedIn has a relatively high number of users (43%) who use it for
less than thirty minutes daily, despite its popularity as the platform of choice for
job-related issues.
7 D S M
On average, a vast majority of Kenyans spend more than one hour daily on social
media. Twenty-eight percent (28%) of social media users in Kenya spend more
than two hours interacting with the social media on a daily basis as shown in
Figure 14. However, a majority (54%) of Kenyans spend less than one hour on
social media per day.
20%
18%
8%
28%
26%
More than 3 hrs
2 - 3 hrs
1 - 2 hrs
30mins - 1 hr
Les than 30 mins
Figure 14:
Daily time spent on Social Media
0 5.0 10.0 15.0 20.0 25.0 30.0
percentages
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
29
Figure 15:
Daily time spent on Social Media
More than
3 hrs
2 - 3 hrs
1 - 2 hrs
30mins - 1 hrLes than 30 mins
Facebo ok
Tw itt er
WhatsApp
Instagram
Snapchat
You Tu be
Linkedln
Facebo ok
Mess enge r
TikTok
Vimeo
Pinterest
Telegram
Skype
0.0 20.0 40.0 60.0 80.0 100.0
27%32%17%7%17%
30%30%16%8%16%
16%25%20%10%30%
28%28%17%9%17%
34%26%15%8%16%
18%27%24%11%21%
43%25%14%6%12%
38%28%14%6%14%
33%26%19%6%16%
35%25%13%6%20%
38%28%14%6%15%
38%24%16%9%13%
36%25%16%9%14%
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
30
8 F B O
Social media users follow brands they admire to learn about products or
services, to get updated with company news, to know about recent promotions
or to connect with people who have similar tastes as themselves. Some people
will also follow a brand as loyal customers who want to communicate with the
organization or to reach out for customer service. Some social media users will
follow a brand during a marketing campaign or when a brand is mentioned by
influencers they like.
From Figure 16, 78% of Kenyans follow brands on social media. 38.9% of the
users aged between 21-25 years old and 30.5% of the 26-25 year-olds follow
their favourite brands online. The older social media users are less likely to
follow brands on social media, with only 12.2% of the those aged between 36-45
years old and 4.9% of the users aged 46 years and above follow brands online.
Urban social media users are more likely to follow brands online than their rural
counterparts. 55.8% of the urban social media users say that they follow brands
online, compared to 44.2% of the rural users.
9 T K S
M
From Figure 17, a majority (52.2%) of Kenyans spend more time on social media
at night and in the evening hours. This could be attributed to the fact that these
are the times of the day when most Kenyans are at home after their day’s work.
Kenyans spend a small amount of time on social media in the mornings, with
only 17.8% accessing these social media sites and apps, which could be linked
to the fact that this is the period most people are busy with their daily routines.
Most Kenyan men (56.4%) spend more time on social media at night, while most
women (47.4%) spend their time on social media platforms in the afternoons.
Not Following Brands
Following Brands
Figure 16:
Foll
owing Brands Online
22%
78%
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
31
A majority of those who are 21-25 years old (40.3%) spend a lot of time
on social media during the night while the older 36-45 year-olds access
the social media in the morning hours. Kenyans residing in rural areas
mostly spend their time on social media in the evenings (45.8%) and
afternoons (45.5%), while urban residents access social media during the
night (56.5%) and in the morning (59.5%).
10 O H
Online harassment is a major problem faced by hundreds of people,
including presidents. Some people have opted to remove their social
media profiles in hopes of avoiding online harassment. The report
adopted the characterization of “less severe” type of online harassment
to include abusive behavior, offensive name-calling, impersonation and
purposeful embarrassment on social media. The report also adopted
classification of “more severe” types of harassment to include physical
threats, stalking, sustained harassment and sexual harassment on social
media.
101 O H – L
The prevalence of “less severe” online harassment among Kenyans is
high, with 33% of social media users in Kenya having personally had a
negative online experience such as abusive behavior, offensive name-
calling, impersonation or purposeful embarrassment in some way. The
experiences with the “less severe” type of online harassment vary by
age, gender and geolocation. From Figure 18, 40% of social media users
aged 21-25 years old and 32% of those aged 26-35 years have personally
experienced the “less severe” forms of online harassment. Therefore,
the younger adults are experiencing an unusually high rate of online
harassment as compared with the older people, as only 4% of social
media users aged more than 45 years reported having experienced
online harassment.
Figure 17:
Time
of the day when Kenyans access Social Media
52.2%
40.3%
24.4%
17.8%
percentages
Night Hours
Evening Hours
Afternoon Hours
Morning Hours
0.0 10.0 20.0 30.0 40.0 50.0 60.0
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
32
While using social media, men are somewhat more likely to experience certain
“less severe” kinds of harassment such as offensive name-calling, impersonation
or purposeful embarrassment compared to women. Fifty-six percent (56%) of
men have had some sort of “less severe” online harassment experience compared
with 44% of women. Urban residents are more likely to experience “less severe”
kinds of harassment than those in rural areas. More than half (55.4%) of the social
media users in urban areas have experienced some type of less severe online
harassment compared to 44.6% of rural area residents. Still, online harassment
is more common among the residents of low-income areas (47.6%) in Nairobi
than those living in the middle-income (28.5%) and high-income (23.9%) areas
(Figure 19).
Figure 18:
Online Ha
rassment by age – Less severe forms
4%
12%
32%
40%
12%
percentages
Above 45yrs
36 - 45 yrs
26 - 45 yrs
21 - 25 yrs
14 - 20 yrs
0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0
Figure 19:
Online Ha
rassment by income levels – Less severe forms
percentages
Low-Income
Middle-Income
High-Income
0.0 10.0 20.0 30.0 40.0 50.0
47.6%
28.5%
23.9%
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
33
102 O H – S
Severe forms of cyber harassment can have serious consequences on the
lives of the victims. 21.1% of Kenyans have experienced the “more severe”
forms of online harassment. Over thirty-eight percent (38.4%) of social
media users aged 21-25 years have personally experienced the “more
severe” forms of online harassment, followed by 26-35 year-olds at 33.6%,
36-45 year-olds at 12.4%, 14-20 year-olds at 11% and 46 years and above at
4.6%. In addition, 53.5% of men and 46.4% of women indicate that they
have experienced online harassment including physical threats, stalking,
sustained harassment and sexual harassment on social media.
Social media harassment is increasingly common and with technology
eliminating the traditional borders, perpetrators of social media facilitated
crimes could be miles away from the victim. Social media facilitated crimes
usually have dreadful real-world impacts on victims. More than two-
thirds (61.3%) of the social media users in urban areas have experienced
some type of severe online harassment compared to 38.7% of rural area
residents. More than half (55.5%) of the residents of the low-income areas
in Nairobi have experienced “more severe” kinds of online harassment,
which is more than twice that (22.1%) of those living in the middle-income
and high-income areas (22.4%), as shown in Figure 20.
55.5%
22.1%
22.4%
percentages
Low-Income
Middle-Income
High-Income
Figure 20:
Target of severe online harassment by income levels, Nairobi
0.0 10.0 20.0 30.0 40.0 50.0 60.0
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
34
11 U P
A pseudonym is a fictitious name used by a social media account-holder to
conceal his or her identity. Whether one should use anonymous online identity
or their real-name when using social media has been a common debate
over the years. The supporters of the use of pseudonyms have indicated that
anonymous identity has its positive functions including its use by people with a
dissenting point of view, whistleblowers, and victims of violence. The people who
argue in support of the use of real names also point out that using one’s real
identity fosters civil discourse and discourages social media trolling, deceiving,
spamming, and cyberbullying. Therefore, the question of whether using or not
using pseudonyms makes one a better online citizen will continue to remain
unanswered. The use of pseudonyms has become common, with 47.7% of
Kenyans using pseudonyms when accessing social media.
The use of pseudonyms in some social and political roles can enrich online
interactions by enabling unfiltered online conversations. Most influencers use
their real names to stand out from the crowd. Most men (57.8%) have used
pseudonyms in online conversations when using social media, compared with
42.1% of women. Over forty percent (40.5%) of social media users aged 21-25 years
old have used pseudonyms in online conversations, followed by 26-35 year-olds
at 28.8%, and 14-20 year-olds at 16.3%. 58.8% of the social media users in urban
areas have used pseudonyms in online conversations compared with 41.2% of
those in rural areas. The use of pseudonyms is common among Nairobi’s low-
income residents, with half of them (50%) having used anonymous identities in
their online conversations. The number of people who have used pseudonyms in
online conversations when using social media is lower among Nairobi’s middle-
income residents at 25.7% and high-income residents at 24.3%.
Research has shown anonymity can lead to negative behavior online, particularly
against women such as trolling, flaming, lurking, and deception, as perpetrators
may be less accountable for the consequences of their actions. Most men (63.1%)
have used pseudonyms on Twitter, whereas most of the women (42.7%) have
used pseudonyms on Facebook online conversations, as highlighted in Figure
21. Social media users aged 14-20 years old (18.2%) and 21-25 years old (43%)
use pseudonyms on Instagram while those aged 26-35 years old (35.5%) and
36-45 years old (12.4%) use pseudonyms on Twitter. Many urban residents use
pseudonyms in online conversations when using Twitter (64%), Instagram (63.1%),
and Facebook (57.7%). 57.3% of Nairobi’s low-income residents use pseudonyms
on Facebook, with 23.6% using them on Twitter, and 20.4% on Instagram. The
middle-income population in Nairobi uses pseudonyms on Facebook (19.6%),
Twitter (46%) and Instagram (44%) while the high-income residents use
pseudonyms on Facebook (23.1%), Twitter (30.3%) and Instagram (35.2%).
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
35
12 M S M
People use social media to get in contact with new people, to keep in
touch with their friends, socializing, entertainment, information seeking,
personal utility and social surveillance or voyeurism and self-promotion,
and exhibitionism.
percentages
Figure 21:
Use of Pseudonyms on specific social media channels by gender
0.0 20.0 40.0 60.0 80.0 100.0
Facebook
Instagram
Twitter
40.5%59.5%
36.9%63.1%
42.7%57.2%
Escape somethings
Mental break from work
Personal identity
Entertainment
Acquiring information
Social interactions
Figure 22:
Motivations for using Social Media
0.05.0 10.0 15.0 20.0 25.
0
percentages
24%
22%
21%
14%
12%
7%
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
36
13 M
The report identifies six motivations for using social media among Kenyans,
which include information acquisition, entertainment, social interactions,
personal identity, a mental break from work, and escaping social realities. The
motivations for using Facebook Messenger (35.4%), WhatsApp (30.8%) and
Telegram (25.8%) are social interactions with family members, friends, and
connection with the outside world, while the motivations for using TikTok (37.1%),
YouTube (33.9%) and Snapchat (30.9%) are for personal entertainment and
pleasure (emotional experiences). On the other hand, the motivations for using
Facebook Messenger (17.7%), Skype (16.5%) and LinkedIn (16%) are to create a
personal identity (personal stability, social status, need for self-respect) while for
LinkedIn (34.5%), Pinterest (25.6%) and Twitter (25.4%) is to acquire information
(news, knowledge, exploration) as indicated in Figure 23. The motivation for
using Vimeo (11.58%), Pinterest (10.6%), and TikTok (10.4%) are to escape societal
realities (release tension, shifting attention from unpleasant happenings).
Most Kenyans access social media from their offices. One of the reasons
employees use social media while at work is to take short mental breaks to
refresh themselves and their minds. The social networking sites and apps
mostly used by employees when they want to take breaks from their work are
TikTok (37.1%), YouTube (33.9%), and Snapchat (30.9%). The use of social media
at work could also help employees in making or supporting their professional
connections and in getting information that could help them solve work-related
problems.
Escape
somethings
Mental break
from work
Personal
identity
EntertainmentAcquiring
information
Social
interactions
Figure 23:
Motivations for using Social Media
percentages
Facebook
Twitter
WhatsApp
Instagram
Snapchat
YouTube
Linkedln
TikTok
Vimeo
Pinterest
Telegram
Skype
Facebook
Messenger
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
26
21 31
22
18
819 35
17
10
13 26 28
14
1415
15
15
916 18
13
12
10 13 16
22 25
21
18
15 25 35
26
23
21
67
68
89
8
510 12
11
8
8
11 12
11 1213 15
11
10 17
14
13
12
12
21
20
16 25 31 34
37
28
28
19
14
13
11
18
12 19
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
37
14 R O B A K
Kenya has a robust blogger community with hundreds of active online
bloggers. Blogs allow individuals and organizations to engage in
discussions with the blog authors and readers over time, facilitating the
exchange of ideas. As such, Kenyans are increasingly turning to blogs
for news, information, politics, and entertainment. Compared with last
year’s data, the number of Kenyans who read online blogs has increased
by 12.9% from 74% in 2019 to 86.9% in 2020. Figure 24 shows the top ten
types of online blogs Kenyans read including Entertainment, Education,
Business, Sports, Politics, Agriculture, Food and Fashion, Health,
environment, and Travel.
percentages
Education
Business
Entertainment
Sports
Politics
Figure 24:
Types of online blogs Kenyans are reading
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.
0
Agriculture
Food & Fashion
Health
Environment
Travel
69.9%
59.9%
47.6%
42.7%
41.3%
40.0%
34.3%
34.3%
22.3%
16.7%
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
38
141 R O B G
Blogs can attract attention and exert considerable influence on individuals,
politics, fashion, and consumer goods. As indicated in Figure 25, most Kenyan
women are reading Food and Fashion (60.4%), Travel (52.1%), and Health blogs
while Kenyan men are regularly reading Sports (69.7%), Politics (64.5%) and
Business blogs (56.7%). While most men read Sports blogs, very few women read
them, and whereas most women read Food and Fashion blogs, very few men
read them, which is a direct opposite in likes and preferences of the two genders
regarding the type of the online blogs they read.
142 R O B G
The rural population mostly read the Travel (48.6%), Health (46.6%) and
Entertainment (46.4%) blogs as compared to the urban residents who mostly
read Business (58.2%), Environment (57.7%) and Education (56.9%) blogs as
indicated in Figure 26.
Figure 25:
Reading Of Online Blogs by Gender
Education
Environment
Entertainment
Sports
Politics
Business
Agriculture
Travel
Health
Food & Fashion
percentages
Female Male
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
43.3
45.3
46.7
44.2
60.4
44.6
51.0
35.4
30.2
52.1
56.7
54.6
53.2
55.7
39.5
55.4
48.9
64.5
69.7
47.9
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
39
143 R O B I N
54.3%46.1%
percentages
Urban Rural
Figure 26:
Reading of Online Blogs by Geolocation
0.0
10.0
20.0
30.0
40.0
50.0
60.0
Education
Environment
Entertainment
Sports
Politics
Business
Agriculture
Travel
Health
Food & Fashion
58.2
56.9
53.6
57.7
54.6
55.3
53.4
55.3
54.6
51.4
41.8
43.1
46.4
42.3
45.4
44.7
46.6
44.7
45.4
48.6
Education
Environment
Entertainment
Sports
Politics
Business
Agriculture
Travel
Health
Food & Fashion
21.7
28.1
31.2
16.5
16.2
22.6
15.0
18.0
29.5
35.1
32.4
33.2
29.6
38.7
36.0
39.7
40.5
35.5
43.5
43.2
39.5
35.6
53.9
45.1
41.4
45.3
41.5
35.0
47.5
9.0
percentages
Low Middle High
Figure 27:
Reading of Online Blogs
by Income levels in Nairobi
0.0
10.0
20.0
30.0
40.0
50.0
60.0
Nairobi’s low-income area residents mostly read Entertainment (31.2%),
Sports (29.5%), and Education (28.1%) blogs. The residents of middle-
income areas in Nairobi read Travel (43.5%), Politics (40.5%), and Health
(39.7%) blogs as shown in Figure 27. Residents of Nairobi’s high-income
areas read Environment (53.9%), Travel (47.5%), and Health (45.2%) blogs.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
40
144 F R O B
Besides facilitating online discussions, communicating information, and
opinions, blogs help individuals to establish identity, status, authority, and
connections among online communities.65% of the blog readers in Kenya read
their favorite blogs daily, 19% read blogs weekly, 5% read blogs monthly while 1%
say they read blogs less often.
15 O D D
Social media is increasingly becoming an important forum for public engagement.
Social media sites and apps offer people the opportunities to have online
discussions and the creation of productive online communities with the potential
for asynchronous online debates. However, engaging in conversations at a distance
on social media is also characterized by a general intolerance for differences in
ideas. It is a common thing for Kenyans to have robust online debates surrounding
contemporary issues in the Kenyan society on social media. More than fifty percent
(57.6%) of the respondents indicated that they have used social media at least once
for online discussions and debates as shown in Figure 29.
Less often
Daily
Weekly
Monthly
65
%
29
%
5%
1%
Figure 28:
Frequency of reading online blogs
Figure 29:
Participation in online discussions and debates
1 - 5 times
6 - 10 times
10+
Not participated
65%
29%
5%
1%
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
41
Public debates are known to influence individual attitudes and
behaviors. SIMElab held thirty-seven focus group discussions with 258
participants in four different counties in 2019. From these focus group
discussions, 43% of the participants indicated that their decisions have
been influenced through online social media debates in four areas:
Politically - shifting from one political party to another.
Personal relationships - when making decision regarding
personal social relationships.
Careers and jobs - when faced with tough career decisions,
online conversations over social media help one to regain self-
control and make the best choice.
Life – when one is making decisions while frustrated, their online
contacts influence the choice one makes.
The focus group discussions also identified thirteen main themes on use
of internet and social media as highlighted in Figure 30.
Figure 30:
Uses of internet among Kenyans
percentages
Socializing
Education
Entertainment
Acquiring
information
Sports
Job search
Politics
Fashion
Religion
Games
Pornography
Dating
0.0 5.0 10.0 15.0 20.0 25.
0
22%
19%
15%
14%
8%
8%
2%
2%
2%
2%
1%
1%
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
42
16 O M, D
F N
Social media has largely facilitated the creation and dissemination of inaccuracies
and falsehoods online. The widespread dissemination of these inaccuracies and
falsehoods on social media has been made worse by the lack of tools for verifying
photos and videos, or for quickly checking the sources of the stories when they
appear on an individual’s Facebook feed, Twitter timeline, YouTube playlist or
any other posts on social networking pages. Most people fail to check the source
of the information that they view on social media before sharing it, which can
lead to fake news spreading quickly or even “going viral”. The only way to stop
spreading misinformation, disinformation, and fake news is for social media
users to stop sharing it. However, the situation is worsened by the use of social
media bots or artificial social media profiles. Social media bots are easily built
using artificial intelligence algorithms to spread inaccuracies and falsehoods
online. For example, social media bots on Twitter are known for tweeting fake
news items, and replying to or commenting on the posts of real social media
users. With Twitter’s deep learning algorithm prioritizing content with greater
prior engagement rather than recent tweets, it is easier to spread fake news
through social media bots as they will keep replying to content that has already
gotten a lot of retweets and mentions. Twitter also provides a summary of the
most interesting Tweets you might not have seen, labeled as “In case you missed
it”.
Misinformation (unintentionally misleading) is false or inaccurate information
that is deliberately created and is intentionally or unintentionally propagated.
Disinformation (intentionally misleading) also refers to inaccurate information
which is usually distinguished from misinformation by the intention of
deception, while fake news refers to false information in the form of news and
which is not necessarily disinformation since it may be unintentionally shared
by innocent users. However, inaccuracies and falsehoods such as gossip, hoaxes,
propaganda, and satire have long been in existence offline and it is only that
social media has created a platform for them, making them accessible by both
human users and artificial bots, deliberately or unintentionally. “Social media
change the self-concept of “citizenry” not only in terms of action (social media
activism) but also in terms of citizenship norms and participatory demands
towards established actors” (Prof. Dr. Martin Emmer, International Symposium
on Social Media, 2019).
161 F, I I I
Most social media sites have been stepping up their efforts to combat the spread
of fake news on their social networking sites and apps. However, this does not
prevent individuals from propagating false and inaccurate information. Most
Kenyans have seen news and information that is false, incorrect, or inaccurate on
social media. Figure 31 shows that over eighty-six percent (86.2%) of Kenyans say
that they have come across false, incorrect, or inaccurate news on social media
and are likely to have shared the misinformation, with only 13.8 % reporting that
they have not come across any false and inaccurate information.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
43
162 I
Some social media users post information that they know is deliberately
misleading, biased, or has manipulated narratives or facts. This could be in
the form of entirely fabricated content created to intentionally disinform
for revenue or influence or to whip up emotions. 83.2% of Kenyans indicate
that they have seen biased and deliberately misleading information on
social media, with 28.3% saying that they do find misleading and biased
information on social media frequently. Just 16.8 % of social media users
report having not seen any deliberately misleading information, while
54.9% find this kind of information occasionally, as shown in Figure 32.
Some of the most common misleading information on social media
include propaganda, clickbait, satire and hoaxes, conspiracy theories,
and pseudoscience.
Figure 31:
False, incorrect or inaccurate information
33.8%
FREQUENTLY
Finds false, incorrect or
innaccurate information
HAVE NOT
52.4
%
OCCASIONALLY
13.8%
Figure 32:
Information that is biased or meant to mislead deliberately online
28.3
%
FREQUENTLY
Finds information that is biased
or meant to mislead deliberately
HAVE NOT
54.9
%
OCCASIONALLY
16.8%
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
44
164 N N
News is typically biased towards negative content. Therefore, social media users are often inundated with
negative news stories such as violence, conflicts, crime, bad economy, natural disasters, terrorism, war,
pandemics, and other upsetting events. Bad news usually stands out and people pay more attention to
it and habitually find it easy sharing it on social media. Young people are more receptive and react more
emotionally to negative political news on Twitter. Research has shown that negative or unfavorable news can
spread very quickly on social media as one negative post by someone influences twice the negative posts
by their online contacts. 81% of Kenyans indicate that they have seen negative news on social media and
are likely to have shared it, with 28% saying that they do find negative news on social media frequently. Just
19 % of social media users have not seen any negative news, while 53% find this negative news occasionally
(Figure 34). Therefore, the majority of news coverage concerns negative topics and is usually directed
towards people’s emotions.
163 F N
Social media is among the primary sources of news in Kenya. Fake news are stories that are not true or have
some truth, but are not 100 percent accurate and are entirely designed to make people believe something
false. However, some people claim that factually accurate stories are fake news, just because they do not
agree with them or find them uncomfortable. It is not easy to spot fake news as most of the time as fake
news also contains a mixture of correct information and could have been shared by trusted friends, family,
colleagues or influential users in the social network, making it difficult to spot what is true and accurate.
People are also likely to react to content that taps into our existing grievances and beliefs. About 83.5% of
Kenyans on social media have come across fake news on social media, and are likely to have shared the
same (Figure 33). 33% have spotted fake news on social media frequently, while 51% find fake news on
social media at least occasionally, with 16% having not come across fake news or not being able to spot the
fake news.
Figure 33:
Fake News Online
33%
FREQUENTLY
Finds Fake News
HAVE NOT SEEN
51%
16.8
%
OCCASIONALLY
Figure 34:
Negative news online
28
%
FREQUENTLY
Finds Negative information
HAVE NOT SEEN
53%
19%
OCCASIONALLY
Conference themes and topics of interest
include (but not limited to):
Theme 1.
Behavioral Approaches to Social Media Research
• Barriers to social media use.
• Drivers for individuals and firms to use social media.
• Social media use for social support, advocacy and awareness-
• Social media use for social support, advocacy and awareness-
building.
• Social media in disinformation and fake News.
• The unintended or unanticipated consequences of using social
media.
• New theoretical perspectives to explain the use of social media.
• Risks associated with using social media.
• The dark sides of using social media.
• The dark sides of using social media.
• Ethical and governance issues related to the use of social media.
• The use of social media for new product development, innovation
management and knowledge management.
• Recommendations and advertising in social networks.
• Social media intoxication, addiction, self-Esteem, and life
satisfaction.
• Use and abuse of social media by adolescents.
• Use and abuse of social media by adolescents.
• Social media commerce.
• Social media brand engagement.
• Social media Effects on our culture.
• How social media influences on daily lives.
• Cyberbullying on social media platforms.
• The dark side of social media.
• Trends in the diffusion of social media platforms (statistics on
• Trends in the diffusion of social media platforms (statistics on
consumer adoption and usage).
• Social media in education.
• Politics and social media.
Theme 2.
Computational Approaches to Social Media research
• Leveraging social media data to inform decisions.
• Social media-related cybercrimes.
• Social media-related cybercrimes.
• Sentiment analysis in social media contents.
• Threat and vulnerability analysis in social networks.
• Prevention of malware propagation in social networks.
• Centrality/influence of social media publications and authors.
• Machine learning in social media analysis.
• Generating Business Intelligence through Social Media Analytics.
@USIUAfrica
Social media have become invaluable tools in nearly every aspect of our daily lives. However, there are
potential and significant risks associated with the use of social media. Globally, the subject of social media
and social media networks have gained interest with most researchers because of their impact on building
virtual communities and networks. Many researchers are now interested in learning more about the social
media platforms and their effects on communities. Therefore, papers are solicited on all aspects of Social
Media and Social Networks with a special emphasis on evidence-based practice and academic papers.
Paper Submission
This is a blind peer-reviewed conference. All submissions will
be subject to double-blind peer-review process. If interested in
participating, submit through the conference website a technical
paper (up to 12 pages), or demo description (up to 2 pages) by
the deadlines given below.
For paper demo queries, contact:
For paper demo queries, contact: simelabadmin@usiu.ac.ke
Important Dates
Conference papers
Papers and Abstracts Due: March 30, 2020
Reviews sent to authors: April 30, 2020
Revised paper due: May 30, 2020
Notification of acceptance: June 30, 2020
Camera-ready due date:
Camera-ready due date: July 30, 2020
Conference dates: September 9-10, 2020
Demos
2 page Demo submission for a 90 minute timeslot session,
should be sent by email to simelabadmin@usiu.ac.ke
Demo Submission: March 30, 2020
Demo Acceptance: April 30, 2020
Submission of Demo Final Paper:
Submission of Demo Final Paper: May 30, 2020
USIU-Africa September 9 - 10, 2020
Theme: Advances in global social media landscape: trends
and newly emerging narratives
2
nd
International Symposium on
Social Media 2020
CALL FOR PAPERS AND DEMOS
Registration
To register visit: www.usiu.ac.ke/issm2020
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
46
SIMELAB Report Launch
USIU-Africa, Nairobi / July 5, 2019
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
47
International Symposium on Social Media
USIU-Africa, Nairobi / September 11-12, 2019
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
48
17 S M DM A
Normally, social media data mining utilizes machine learning, mathematics,
and statistical techniques to uncover hidden patterns and trends from social
media sites and apps and to visualize the results in a way larger audiences
can understand. This is achieved through automated software programs that
sift through massive amounts of raw social media data in order to discern
patterns, and trends. The identified patterns, trends and metrics can be used in
designing organizational growth strategies.
171 A S N A #KC H
SIMElab as an interdisciplinary Center
for research in Big Data and Social
Media Analytics has a team that
works on social media data mining
and analysis on various topics. The
team works with both graduate and
undergraduate students, civil society,
and corporates on social media data
mining and analysis. The team has
been monitoring conversations on the
#KomeshaCorona hashtag on Twitter
and did a Social Network Analysis on
the hashtag.
Through social network and
graph theory lenses, this article
explored Twitter data shortly after
the announcement of the first
COVID-19 case in Kenya and the use
of #KomeshaCorona hashtag. The
study used social media analytics
tools ‘Network Overview, Discovery
and Exploration for Excel (NodeXL)
and Brandwatch to extract and
visually present knowledge from
pairwise relations between actors in
the #KomeshaCorona hashtag social
network. In social network analysis,
a large number of measures have
been developed to characterize
and compare network structures
and positions in networks. Data
collected for Social Network Analysis
(SNA) are analyzed by means of
several techniques that illustrate the
relationships. The analysis can be
focused on differences in centrality,
on the investigation of strongly
connected clusters, of positions
that are structurally equivalent in
networks, or of unique positions or a
comparison of network structures as
a whole. The use of network metrics
helps identify who is most important
or central in a network, subgroups
(i.e., network clusters) of tightly
connected people, and the overall
network structure (e.g., the density of
a network). Social networks are made
up of vertices (e.g., people) that are
connected to one another via edges
(e.g., friendship ties).
The purpose of the study was to
identify the social media users
who were the influencers in the
#KomeshaCorona online discussions
between March 2020 and June 2020.
The study objective was to determine
the key influential actors on the Kenyan
social media in the #KomeshaCorona
conversation and the distributions
of relationships between social
media users in the #KomeshaCorona
conversation. The study approach was
quantitative research methodology
By Patrick Kanyi Wamuyu, Jacktone Momanyi and
David Lomoywara, SIMELab
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
49
with data collection done using
Social media data mining through
NodeXL and Brandwatch APIs.
Data analysis was achieved
through the interpretation of
quantitative social network graph
metrics. These graph metrics
include vertex metrics related
to networks such as degree, in-
degree, out-degree, betweenness
centrality, eigenvector centrality,
closeness centrality, PageRank,
and clustering coefficient that
can be used to identify unique
or important people within a
network.
Twitter is considered as one of the
most dominant and persuasive
social media platforms today
(Sanawi, Samani & Taibi, 2017).
Twitter is a microblogging site
created in 2006. Microblogging is a
form of blogging that allows users
to send brief text (microposts)
updates or micromedia such as
photographs or audio clips. Other
microblogging services include
Plurk, Tumblr, Sina Weibo, and
Soup.io. Twitter currently has
a text limit of 280 characters.
Twitter supports social networking
through “friending” or “following”
and large-scale sharing and
diffusion of information (Bruns &
Burgess, 2011). Twitter users use
hashtags, which consist of brief
keywords or abbreviations with a
prefixed hash symbol for effective
communication with an ad hoc
community sharing the same
concerns or topics of interest.
Opinion leaders are those
individuals who are more
connected than others and thus
are more likely to influence the flow
of information by facilitating the
dissemination of media messages
to audiences.
Network analysis techniques have
been adopted to explore opinion
leaders within the structure of
social relationships as opinion
leaders take up strategically
beneficial positions in a network
(Xu et al., 2014). However, there is no
standard way to identify and define
influential users’ in online social
networks (Mahmoudi, Yaakub &
Bakar, 2018). Opinion leadership
in this study is measured using
in-degree centrality, betweenness
centrality, and eigenvector
centrality.
The Network Overview, Discovery
and Exploration for Excel (NodeXL)
is a Microsoft Excel add-in
template which allows users to
generate social network graphs for
social media network analysis and
visualization. NodeXL can harvest
data from a variety of sources
including Twitter, YouTube, Flickr,
email, and WWW hyperlinks.
The study used NodeXL Version
1.0.1.433.
Data was collected using the
NodeXL Twitter Search Network
data collector to get tweets having
each of the study blogs hashtags,
tweets, retweets, or mentions of
the hashtag #KomeshaCorona.
The network structure was
analyzed quantitatively and
represented visually using the
Clauset-Newman-Moore Cluster
layout algorithm and the Harel-
Koren Fast Multiscale layout
algorithm.
The mine generated the
#KomeshaCorona network
structure which contained a total
of 13323 edges (including 6098
unique edges and 7225 edges
with duplicates) and 3848 vertices
identified using NodeXL.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
50
The edges in this study were all
presented as directed edges. These
mined edges included Replies to,
Mentions, Retweet, Mentions in
Retweet, and Tweets. Figure 35
illustrates the network graph according
to the Harel‐Koren multiscale layout
algorithm, a visual representation of
the overall networked data from the
#KomeshaCorona hashtag showing
the clusters and indicating the
influencers on the social network.
Each circle corresponds to a node
or Twitter user, the size and opacity
of each user is proportional to
their Eigenvector centrality value,
while the color corresponds to sub-
communities or clusters automatically
identified. The larger circles made of
connected nodes represent a group.
These groups are clustered according
to their relative network density,
displaying users with high network
density. The users with a lesser degree
of network density are isolated cases
at the bottom right-hand corner of
Figure 35 as they fail to impact the
overall visualization of the clusters
because they do not communicate
with others in the network.
Identifying the most important
vertices (users) in a graph is usually
based on the ranking in the social
network graph centrality metrics
(Struweg, 2020). Degree centrality
is a count of the total number of
connections linked to a particular
vertex (user), i.e. the total number
of edges it has. Nodes with high
centrality degrees also have high
centrality by other measures. Out-
degree is the number of arrows
directed away from the vertex (user).
Out-degree centrality is the measure
of influence in the network. The
user with the highest out-degree
calculation is then referred to as
the main influencer in the network.
In-Degree is the number of edges
(arrows) that point toward the vertex
(user) of interest in the network. In-
degree value is the number of Twitter
users that replied to or mentioned
the study hashtag, #KomeshaCorona.
In-degree centrality is a measure of
popularity in the network. Ministry
of Health (@MOH_Kenya) is the top
user in both the out-degree and the
in-degree an indication of opinion
leadership in both popularity and
influence.
Figure 35: #KomeshaCorona Eigenvector Centrality graph
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
51
Eigenvector centrality measures
a user’s importance while
considering the importance
of the neighbors in the
network structure, i.e. a user is
important if they are linked to
other important users. Higher
eigenvector centrality indicates
quality connections with other
users who are well connected.
Therefore, being connected
to certain users in a network
structure is more beneficial than
a connection to others. High
Eigenvector centrality value
indicates a strong influence
over other nodes in the social
network structure. Betweenness
centrality measures the extent
that the user falls on the shortest
path between other pairs of users
in the network.
It is the degree to which a vertex
plays the bridging role in a
network. The more people depend
on a user to make connections
with other people, the higher that
user’s betweenness centrality
becomes. Twitter accounts with
many short paths have high
betweenness centrality and
are considered as influential
information gatekeepers
(Struweg, 2020). Users with
high eigenvector centrality
in the network are centers of
attention, whereas users with
high betweenness centrality in
the same network are information
brokers. The user @MOH_Kenya
has the highest eigenvector
centrality and betweenness
centrality among the Twitter
users in the #KomeshaCorona
network structure. “Betweenness
and eigenvector centralities
have very desirable properties
for the location of an influencing
potential” (Litterio et al., 2017,
pp. 355). A member of the
Online Social Network Structure
who simultaneously meets
the highest values of both
betweenness and eigenvector
centrality are classified as
influencers, hence @MOH_Kenya
is an influencer among Twitter
users in the “Komesha Corona”
online conversations in Twitter.
Table 1, provides a summary of
the #KomeshaCorona hashtag
social network graph metrics.
The most popular Twitter user
accounts in the #KomeshaCorona
conversations on Twitter are;
@MOH_Kenya,
@SpokespersonGoK,
@WHOKenya,
@Consumers_Kenya,
@CrimeSiPoaKenya,
@KeCheza.
Using in-degree values, the
Twitter users with the highest
value in the #KomeshaCorona
online conversations were the
Ministry of Health, followed by
the Official Twitter account
of the Government of Kenya
Spokesperson, and World Health
Organization in Kenya. Therefore,
the Ministry of Health is the most
popular and influential Twitter
user in the #KomeshaCorona
social network.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
52
Top 3 Twitter Users, Ranked by In-Degree In-Degree
@MOH_Kenya 2005
@SpokespersonGoK 151
@WHOKenya 116
Top 3 Twitter Users, Ranked by Betweenness Centrality Betweenness Centrality
@MOH_Kenya 9301840.638
@Consumers_Kenya 302209.2472
@SpokespersonGoK 291757.3067
Top 3 Twitter Users, Ranked by Eigenvector Centrality Eigenvector Centrality
@MOH_Kenya 0.020667
@WHOKenya 0.002182
@SpokespersonGoK 0.002065
Top 3 Twitter Users, Ranked by Out-Degree Out-Degree
@MOH_Kenya 40
@Crimesipoakenya 34
@kecheza 28
Based on the out-degree values
generated by NodeXL, the top three
most popular Twitter accounts are
the Ministry of Health, followed by
Crime Si Poa (crime is not cool),
an anti-crime advocacy and lobby
group, and a Twitter user using a
pseudonym ChezaKe. Therefore, the
Ministry of health is the most popular
and influential Twitter user in the
#KomeshaCorona social network.
Using Betweenness Centrality values,
the Twitter user with the highest
value in the #KomeshaCorona online
conversations was the Ministry of
Health, followed by the World Health
Organization in Kenya and the Official
Twitter account of the Government of
Kenya Spokesperson. Therefore, the
Ministry of Health is the most popular
and influential Twitter user in the
#KomeshaCorona social network.
Based on the Eigenvector Centrality
values generated by NodeXL, the top
three most popular Twitter accounts
are Ministry of Health, followed by the
Consumer Grassroots Association,
a consumer protection, education,
and advocacy organization and
lobby group, and the Official Twitter
account of the Government of
Kenya Spokesperson. Therefore, the
Ministry of Health is the most popular
and influential Twitter user in the
#KomeshaCorona social network.
With the names of individuals and
non-governmental organizations
(NGOs) outside the government and
government agencies appearing
among top influencers, it is a good
indication of public interaction
in social media concerning the
Coronavirus pandemic.
Table 1: Graph Metrics for the #KomeshaCorona
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
53
From the Twitter data mined using Brandwatch, it is clear that the online
conversations among Kenyans on Coronavirus is fizzling out as evidenced
by the number of mentions of the hashtags #KomeshaCorona, #staysafe
and #COVID19KE on Twitter discussions in the month of June 2020 as
shown in Figure 36.
Figure 36: #KomeshaCorona Mention Volumes for the last three months
The word cloud below, Figure 37, generated by Brandwatch, shows that the
#KomeshaCorona hashtag was the most mentioned “word” among Twitter
conversations between individuals based on #covid_19KE, #KomeshaCorona,
#COVID19KE, #MOH_Kenya and #WHOKenya between March 2020 and Jun
23, 2020. The names of individuals outside the Government and Government
Agencies appearing in the cloud are a good indicator of public participation in
social media discussions about the Coronavirus pandemic.
Figure 37: Word cloud generated f rom Brandwatch for the online conversation
on COVID-19 in June 2020
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
54
References
1. Bruns, A. and Burgess, J. (2012). Researching News Discussion on Twitter.
Journalism Studies,13(5-6),pp. 801-814.
2. Litterio, A. M., Nantes, E. A., Larrosa, J. M., & Gómez, L. J. (2017). Marketing and
social networks: a criterion for detecting opinion leaders. European Journal of
Management and Business Economics, 26(3), pp. 2444-8451.
3. Mahmoudi, A., Yaakub, M. R. & Bakar, A. A. (2018) New time-based model to
identify the influential users in online social networks. Data Technologies and
Applications, 52, pp. 278-290.
4. Sanawi, J., Samani, M.C & Taibi, M. (2017). #Vaccination: Identifying Influencers
in the Vaccination Discussion on Twitter Through Social Network Visualisation.
International Journal of Business and Society, 8(S4), pp. 718-726.
5. Struweg I. (2020). A Twitter Social Network Analysis: The South African Health
Insurance Bill Case. In: Hattingh M., Matthee M., Smuts H., Pappas I., Dwivedi
Y., Mäntymäki M. (eds) Responsible Design, Implementation and Use of
Information and Communication Technology. I3E 2020. Lecture Notes in
Computer Science, vol 12067. Springer, Cham.
6. Xu, W.W., Sang, Y., Blasiola, S. & Park, H.W. (2014). Predicting opinion leaders in
twitter activism networks: the case of the Wisconsin recall election. American
Behavioral Scientist, 58(10), pp. 1278-1293.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
55
18 C
Preface
Social media has enormously developed
in the past decade, from rudimental social
media sites offering low-level services to
high-tech mobile social media sites and apps
with a vast number of services, attracting
millions of daily users. Social media was
once seen as a communications channel
between family, friends, and colleagues at
work, but now has transformed all spheres
of everyday life from social interactions,
news and journalism, food and fashion,
entertainment, business, and research with
incredible influence on people’s lives.
It is therefore important to think about where social media is heading and
the trends that are defining the current and future generation of users.
Hate speech, addiction to our digital identities and social media use,
anonymity, privacy, social media marketing, entry of new social media
channels, changes in social media consumer demands and how all these
will define the future of content creation and consumption in social media
are some of the areas of interest that have been highlighted in this report.
The commentaries put together by a knowledgeable team of experts all
seek to answer this question: Social media use has grown beyond personal
use, what next? Consequently, we have commentaries on: social media
as a cause of hate speech; trends in social media marketing; how social
media will be in the new decade; social media addiction; understanding
online consumer audiences; user anonymity on social media; and what
brands can learn from listening to consumers’ online conversations.
The commentary also addresses the ongoing global COVID-19 pandemic,
with a focus on misinformation and COVID-19; influencer marketing and
consumer behavior post-COVID-19; harnessing social media consumption
in fighting the COVID-19 pandemic among the youth; dealing with
COVID-19 pandemic stigma; social media usage during COVID-19 in
Kenya; and fake news on social media during the pandemic.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
56
181 M COVID-19
Melissa Tully, Associate Professor, School of Journalism and Mass
Communication, University of Iowa, USA
It should come as no surprise that
misinformation around COVID-19
is spreading on social media and
chat apps, like WhatsApp, given our
everyday experience with health
misinformation online before
the pandemic. Misinformation
surrounding how diseases spread,
vaccinations, cures, diets, exercise
and other personal and public
health are commonly posted and
shared on social media sites and
chat apps. Although misinformation
surrounding vaccines has led
to well-known fears and anti-
vaccination movements, other
kinds of health misinformation
circulates, often unchecked, leading
to misperceptions and unsafe
behaviors.
March 2020 survey data show that
Kenyans, Nigerians, and South
Africans get much of their news and
information about COVID-19 on social
media, with 47% of respondents
saying that social media is a primary
source for information about the
coronavirus. In addition, 75% of
respondents said they had seen
information about coronavirus on
WhatsApp; and many were skeptical
about this information, with 66%
of respondents rating it as only
“somewhat truthful” (Elliott, 2020).
While this skepticism is important
and shows that respondents are
not taking posts at face value, it
does not tell us how people find
quality information that is critical
for understanding the virus and for
making informed health choices.
While government regulations
and social media company policies
have been suggested as a means
of combating the spread of
misinformation online, and have
received renewed interest given the
spread of COVID-19 misinformation,
these steps often come at the cost
of free speech (in the case of many
laws governing “fake news” around
the world) or are too minor to create
real change (in the case of many
social media policies). Although
well-thought out and developed
regulations and policies should be
part of a response to misinformation,
social media users can also be
mobilized to stop the spread of
misinformation and to correct it
when they see it (Bode & Vraga, 2020).
Importantly, we, as social media
users, can develop knowledge and
skills that make us more savvy
news and information consumers,
enabling us to discern low- and high-
quality information, to verify and
seek additional information when
we’re unsure of the veracity of a post,
and to correct misinformation when
we see it by providing evidence and
links to quality news and information
(Tully, Vraga, & Bode, 2020). If we take
steps to improve our knowledge and
skills, we can part of the solution to
stopping misinformation rather than
the problem.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
57
References
1. Bode, L., & Vraga, E. (2020, March 7). Americans are fighting coronavirus
misinformation on social media. The Washington Post. Retrieved from
https://www.washingtonpost.com/politics/2020/05/07/americans-are-
fighting-coronavirus-misinformation-social-media/
2. Elliott, R. (2020, March 17). Report: Coronavirus in Sub-Saharan Africa.
GeoPoll. Retrieved from https://www.geopoll.com/blog/coronavirus-africa/
3. Tully, M., Vraga, E. K., & Bode, L. (2020). Designing and testing news literacy
messages for social media. Mass Communication and Society, 23(1), 22–46.
doi: 10.1080/15205436.2019.1604970
182 I -
COVID-19
Japheth Mursi, University of KwaZulu-Natal
Consumer behavior has evolved
drastically since the advent of
COVID-19. COVID-19’s global rise
has disrupted people’s way of
living and has changed their
personal and professional lives.
These new behaviors will change
the way people engage and
will certainly continue to lead
changes in consumer preferences.
For companies, marketers and
advertisers will need to revisit
their marketing strategies before
COVID-19. According to Mathew
(2020), Marketing after a pandemic
will be a challenge, as companies
will need to be sensitive and
cognizant of what consumers have
been through. In order to adapt
to this new norm post- COVID-19,
businesses will have to increase
their digital presence and adopt
modern marketing approaches like
influencer marketing. Influencers
play a unique role of being actors
in this diversion through content
creation, which takes away
consumers’ minds from isolation
(Media Update, 2020).
A report by Takumi (2020) posited
that 60% of 16 to 24-year-olds credit
influencers for a recent purchase.
According to Media Update
(2020), present consumers are
more accustomed to using digital
technology to socialize and have
been conditioned to buy products
from people they have used or
trust. Therefore, going forward,
social media influencers will
continue to be a credible source of
information and an effective form
of marketing that is crucial to new
consumer behavior. Consulting
company Kantar found that social
media engagement in later stages
of the pandemic has increased by
61 percent over normal usage rates.
The use of video platforms is also
steadily increasing as celebrities
and brands leverage social
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
58
media Live platforms to entertain
and connect with their audiences.
In March, TikTok saw a 27 percent
increase in downloads from February,
with 6.2 million downloads. This
implies the increase of social media
use won’t fade after ‘lockdowns’ are
lifted in various countries (Johnson,
2020).
As people continue to social distance,
influencer marketing provides a
feeling of community that others
lack. As people isolate themselves
socially, influencer marketing
provides a sense of community
that others require. Mostly when
companies are promoting a product
or service, the ultimate purpose is
to create a community around this
product or service that can now
be done easily by Influencers. Post
COVID-19, consumers will look for
brands that can translate their online
experiences, bring communities
together, facilitate participation and
encourage emotional engagement.
Influence Central, a marketing firm,
found that consumers appreciate
brands that have shown a focus on
consumers’ needs during a difficult,
unprecedented time (Pastore, 2020).
Fifty-eight percent of consumers
said they were thrilled by brands
providing a necessary service, and 55
percent said they treasured brands
that have made changes to help
consumers. Therefore, as consumer
behavior continues to change due
to the ongoing pandemic, influencer
marketing will further strengthen
its position as an essential and a
necessary marketing strategy post-
COVID-19. Companies must be ready
to serve a consumer base with a
completely different preference,
behavior, and opinions with different
strategies.
References
1. Mathew, J. (2020, 04 25). Post COVID-19: Will consumer behaviour patterns
mutate? Retrieved from Brandequity: https://brandequity.economictimes.
indiatimes.com/news/marketing/post-covid-19-will-consumer-behaviour-
patterns-mutate/75369733
2. Johnson, T. (2020, 04 21). The Rise of TikTok During COVID-19. Retrieved from
Tinuiti: https://tinuiti.com/blog/marketing-news-covid-19/tiktok-covid-19/
3. Media Update. (2020, 04 10). COVID-19’s effect on influencer marketing. Retrieved
from mediaupdate: https://www.mediaupdate.co.za/marketing/148378/covid-
19s-effect-on-influencer-marketing
4. Pastore, A. (2020, 04 20). Consumer Behavior in a Post-COVID-19 World. Retrieved
from WWD: https://wwd.com/business-news/business-features/consumer-
behavior-reports-predict-a-post-covid-world-1203562275/
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
59
183 S M C H
Martin Emmer, Freie Universität Berlin & Weizenbaum
Institute for the Networked Society
Social Media opened up not only
the gates for new forms of self-
expression and participation, it
has at the same time flooded the
internet with harmful content like
fake news and hate speech. New
data from a survey in Germany
show that more than half of all
internet users in the country have
encountered hate speech online
(Schaetz et al., 2020, p. 9). As there
are quite similar developments
in many countries around the
globe, including Kenya (Kimotho &
Nyaga, 2016), it is widely discussed
whether political culture might be
eroding, with the internet as the
cause of radicalization of online
users and public discourse.
However, there are characteristics
of social media that may mitigate
such concerns. First, when
focusing on the source side of
harmful content, a different
picture emerges: Studies show
that it often is only a small number
of accounts that is responsible for
posting and sharing the majority
of propaganda or hate postings
(Grinberg et al., 2019; Schaetz et
al., 2020). Second, we must not
underestimate the fact that social
media are blurring the boundaries
between private and public. A
large amount of incivility and
rumors on social media may not
be a completely new phenomenon
caused by radicalizing social media,
but may be a quite frequent and
normal form of social interaction
that just has suddenly been
made visible for the public in the
new digital media environment.
Third, indicators of social trust and
support for democratic norms in
our societies is still high and yet
seems not to be affected by this
potentially dangerous content on
social media (Schaetz et al., 2020,
p. 7).
Even if we should be careful to not
draw superficial conclusions from
social media content on possible
causes, there still are reasons for
concern: First, all data currently
available just covers a short
period of time since social media
emerged, and effects of harmful
content on users and societies
still may be possible in the long
run. Second, even if just a small
number of users are affected, this
still may cause dramatic harm
to citizens and societies in the
case of misled individuals being
mobilized to violent action and
committing excessive crimes like
in the Christchurch mass murder
of March 15, 2019. While there is
no reason for panic, hate speech
and other harmful content still
represent a danger to modern
society, that needs further and
thorough research.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
60
References
1. Grinberg, N., Joseph, K., Friedland, L., Swire-Thompson, B., & Lazer, D. (2019). Fake
news on Twitter during the 2016 U.S. presidential election. Science, 363(6425),
374-378. doi:10.1126/science.aau2706
2. Kimotho, S. G., & Nyaga, R. N. (2016). Digitized Ethnic Hate Speech: Unterstanding
the Effects of Digital Media Hate Speech on Citizen Journalism in Kenya. Advances
in Language and Literary Studies, 7(3), 189-200. doi:10.7575/aiac.alls
3. Schaetz, N., Leißner, L., Porten-Cheé, P., Emmer, M., & Strippel, C. (2020).
Weizenbaum Report: Politische Partizipation in Deutschland 2019 (Political
Participation in Germany 2019). Berlin: Weizenbaum Institute. doi:10.34669/
wi.wr/1
184 S
Brian Kisuke, COMZTECH
Elaborating the difference between
a fact and a truth, Martin Luther King
Jr. in a 1965 speech to UCLA students
and faculty said ‘a fact is the absence
of contradiction. Truth is the presence
of coherence, the relatedness of facts’.
Little did he know that 55 years later,
we would be sharing alternate facts
in media outlets. Conveniently, social
media platforms have seen the brunt
of excessive use of alternate facts. This
is because posts are rarely monitored
and put to task for authenticity.
The non-monitoring is nevertheless
an advantage since it allows for
discussions which bring to light
underlying conditions in the society.
The new decade 2020 – 2030 will
experience introductions of new social
media apps into the market as others
fade out. The apps which will survive
the decade will have to adhere to user
privacy, keep up with security and
design flaws and innovate constantly.
First, the implementation of General
Data Protection Regulation (GDPR)
in May 2018 on privacy and data
protection for European Union
members was a wakeup call to social
media giants. Considering the law is
about user data, social media sites
are adversely affected as they are
hoarders of personal information.
The law imposes fines to companies
that flout it. In fact, Google is in the
top five list of companies fined for
violating the law. And other cases are
under investigation. Essentially social
media companies to stay relevant will
have to follow the regional and global
privacy regulations.
Secondly, security and design flaws
will continue to be important features
on new apps. Before the rhyming
name app, TikTok was born, there was
YikYak. YikYak was an anonymous
messaging app based on user’s
geographic vicinity. Unfortunately, its
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
61
anonymity of users contributed
to its downfall. It was the norm to
have cyber bullying, hate speech,
gun and bombing threats from
users. Understandably, unable to
address the security issue it was
forced to shut down. Lastly, the
latest culprit of engineering flaws
was Google+ which was closed
in April 2019 due to low user
engagement and design flaws.
Innovating with emphasis on
features which users find relative
is the third and important factor
for relativity in the new decade.
A case in point of the last decade
was Meerkat app which had an
innovative idea of live-streaming
in social media feeds. However,
Meerkat was slow in adding other
features and this saw Instagram
and Facebook duplicate the
feature and render Meerkat
worthless. It closed in 2016.
Another app was Vine which was
shut down by Twitter in 2016. For
those who do not remember, it
was a video loop app that offered
users a platform to make and share
six second videos. Unfortunately,
most people started using
Instagram instead because in
addition to posting videos users
could post pictures and it had a
friendlier user interface.
Currently there are competing
apps in the messaging realm.
Telegram, an alternative
messaging app to WhatsApp
offers more secure chats from
features like secret chats, self-
destructing messages and larger
group capacity. The features have
an audience who prefer to toggle
back and forth between the two.
And as recently as June 18 2020,
Google announced a new service,
Google Keen. Keen is “a place to
grow and share your interests with
loved ones, and find things that
will help in making this precious
life count”. Basically, a competitor
to Pinterest.
Innovation includes other
salient features like curbing the
propensity of alternate facts posts
from users. The global events of
2020 like COVID-19 and Police
brutality protests have forced
Facebook and Twitter to initiate
a policy for tagging misleading
information and alternate facts,
which is a feature demanded
and initiated by users. Another
feature initiated by Facebook
allowing users to opt out of
election advertisements in the
upcoming US general election
will make it stay relevant with end
users. Innovating as fast as users’
request will enable apps stay
relative and hence keep users.
A Pew research survey conducted
in Spring 2017 titled Global
Attitudes survey indicated that
the global median use of social
media use is 53% of adults.
Although Kenya ranked below the
median at 30% it is expected that
the usage will climb up through
the decade because majority of
the users at the time of the survey
were young adults aged between
18-36. As the decade progresses
surely these young adults will
pave way for teenagers to be
counted as adults in their use of
social media. Therefore, the usage
of social media will continue to
grow in the new decade.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
62
In summary, the social media apps which will last through the decade must stay
relevant by addressing user privacy and adhering to regulatory bodies, security
and design flaws and innovation of its users.
References
1. http://medienorge.uib.no/files/Eksterne_pub/Pew-Research-Center_Global-Tech-
Social-Media-Use_2018.06.19.pdf
185 H S M C F
COVID-19 P Y
Dr. Geoffrey Sikolia, Assistant Professor of Mass Communication,
USIU-Africa
In December 2019, the first case of
the respiratory disease coronavirus
(COVID-19) was reported in Wuhan,
Hubei province of China. This led
to a global disruption of all sectors
and upgrading of the disease to a
pandemic, with global infections
and fatalities spiraling significantly.
Africa has not been spared. The
weak healthcare systems across the
continent present a serious threat.
The continent therefore could harness
the use of social media, whose
consumption keeps rising, to stem the
spread of this pandemic and manage
the areas already affected. The youth
population in Africa is among the
highest globally. As a consequence,
social media consumption continues
to raise concern among key
stakeholders as to the user needs and
gratifications sought by the youth.
The Internet is primarily intended
for learning and research and has
become an important component
of life. However, from time to time,
cases of over-involvement with the
Internet among the youth raise alarm.
Although research reports an upward
trend in the penetration of new
media technologies in Africa, several
obstacles to access are outlined.
These include income disparities
between rural and urban populations,
limited bandwidth and consistent
power outages, high costs associated
with acquisition and maintenance of
mobile phones, and infrastructure
constraints.
The youth are generally motivated by
the desire to bond and bridge social
capital, entertainment, and escape
through the consumption of social
media. That the youth in Africa are
seeking these gratifications in their
social media usage is encouraging.
These technologies could be
harnessed to enhance contact
tracing and COVID-19 behavior
change campaigns among the youth
on the continent. Social media can
also enable the mapping of existing
healthcare resources to ensure
preparedness among health workers.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
63
186 D P S: S M U
D COVID-19 K
David Lomoywara, SIMElab
Since the time coronavirus erupted
in Wuhan, China, the issue of social
stigma has become a bigger
global problem than the virus itself.
According to the World Health
Organization, social stigma is the
negative association between a
person or group of people who
share specific characteristics.
Goffman, one of the influential
sociologists, defined stigma as an
attribute that conveys devalued
stereotypes. It is a phenomenon
in which a person with a deeply
discreditable trait is seen as
different from those who believe
they are healthy.
Kenya reported the first case of
the virus in March 2020. To many
Kenyans, the virus was an alien
disease only found in China. Reality
hit Kenyans hard when the first
case was reported in Nairobi. This
caused a lot of panic and fear of
uncertainty. Those suspected of
having contracted the virus were
quarantined at Mbagathi Hospital
for testing, and those whose
results turned positive were taken
into isolation. As the number of
infected people increased, the
issue of social stigma worsened.
The first incident happened in
Kilifi County, where a person
suspected of having the virus was
lynched by youth at night while
he was going home. The issue
continued to worsen, and the
mainstream media reported cases
of discrimination and neglect
meted against those suspected
of having the virus. In Murang’a
and Naivasha, some individuals
were neglected by their families,
due to the suspicion that they had
contracted the virus. In Nairobi and
Mombasa, those who wanted to
travel upcountry felt stigmatized
because of the increased cases
reported in the two cities.
Nonetheless, to avert the situation,
Kenyans on social media platforms
joined the bandwagon to create
awareness about the coronavirus.
A young girl by the name Salome
Wairimu sang a song dubbed
“Janga La Corona,” (coronavirus
catastrophe) in April, which
garnered more than one million
views on YouTube within a week.
Twitter trended with famous
hashtags such as KomeshaCorona,
Covid19KE, Covid19, StaySafe,
Stay Home. These hashtags were
used by Kenyans on Twitter to
discuss the pandemic and how to
normalize the virus’ effects.
Facebook users actively deviated
from the usual ways of doing things
and adapted to the new normal.
Some showed their skills by posting
short videos on cooking recipes,
while others taught students
key lessons such as Chemistry
and Mathematics. An emerging
TikTok became a platform where
many escaped realities and posted
short, entertaining videos. All the
strategies employed on social
media were vital in normalizing the
stigmatizing effects of coronavirus.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
64
187 S M F N COVID-19 P
Ernest Mwanzi, Senior Digital Marketing & Communications Officer,
USIU-Africa
Dictionary.com defines Fake News
as false news stories, often of a
sensational nature, created to be
widely shared or distributed for the
purpose of generating revenue,
or promoting or discrediting a
public figure, political movement,
company, etc. However, some writers
have argued that the term False
Information is more appropriate as
“Fake News” is mostly appealing and
used in the political arena.
Since the beginning of the COVID-19
pandemic, various reports have
shown that fake news has taken root
all across the world. For instance, US
President, Donald Trump, has been
quoted as saying that ingesting
disinfectants could potentially be used
to treat coronavirus. Locally, there was
information widely circulating saying
that the coronavirus could not survive
the tropical climate, reducing our risk
of exposure to it.
The Ministry of Health in Kenya (MOH)
and the World Health organization
(WHO) have been on the forefront
in fighting fake news by providing
platforms which people can verify
any information about COVID-19.
The Ministry of Health, for instance,
has been active on Twitter, providing
frequent updates and information
on the coronavirus, while the
World Health Organization has an
automated WhatsApp line through
which people can get information on
the virus instantly and at any time.
Social media companies such has
Facebook and Twitter have also taken
the lead in fighting this pandemic
by having anchor posts on their
respective platforms with verified
information related to the virus.
For these reasons USIU-Africa
through the Social Media Lab realized
the need to host a webinar to tackle
the emergent issue on “Social media
Fake News and Mental Health in the
Age of COVID-19”. The webinar, which
was held on Thursday, June 4, 2020,
brought speakers from both the
Academia and industry experts to
discuss Fake News and their effects
on mental health
Prof. Melissa Tully, Associate Professor,
School of Journalism and Mass
Communication, University of Iowa
noted that the pandemic presented
a set of unique communication
challenges due to the level of
uncertainties revolving around health
issues and thus making it easy to
spread fake news.
She reiterated the dangers of
spreading fake news, adding that
governments should invest on
practical research that can help in
coming up with practical solutions
to empower people not to share
misinformation and how to find
quality information.
“There are many ways of ignoring
online information that can’t be
authenticated in circulating, but we all
need to take responsibility and politely
advise any users, especially those
on closed sites such as WhatsApp,
against spreading fake news without
substantiated facts. Now, more than
ever, it is crucial to ensure that we
use our time constructively by doing
things that take our thumbs away
from our smartphones, “she said.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
65
Dr. Stephen Ndegwa, a clinical
psychologist noted that fake news
was like adding salt to injury, as it
multiplied the anxiety that came
with COVID-19. “As social beings,
when we are put in isolation,
and are unable to verify any
information received, it causes
stress, thereby affecting our
mental health even further, “he
said. Mr. Philip Ogolla, Founder
Digital Humanitarian and New
Media Consultant indicated that
our Health workers are strained
and battling fatigue and that
misinformation on COVID-19
demotivates them further.
“Fake news in the country is spread
by individuals who want to be first
to break news, with some of them
going to the extent of creating
screenshots and fake quotes. I
know some families affected by
coronavirus who no longer go
online or visit social media sites,
because of the misinformation
around the pandemic,” he noted.
He also underlined the need
of using all digital platforms to
capture testimonies that can
educate and create awareness
of the pandemic and to all who
deliberately think they won’t
become victims – adding that
for most Kenyans, this pandemic
only becomes a reality once it hits
closer home. Philip urged all to use
the available credible resources,
such as the WHO website, which
has real time statistics and facts of
the ongoing pandemic.
According to the UNESCO
Handbook for Journalism
Education and Training; Fake
News is an old story, fueled by
new technology; mobilizing and
manipulating information was
a feature of history long before
modern journalism established
standards which define news
as a genre based on particular
rules of integrity. An early record
dates back to ancient Rome,
when Antony met Cleopatra
and his political enemy Octavian
launched a smear campaign
against him with “short, sharp
slogans written upon coins in
the style of archaic Tweets. “The
perpetrator became the first
Roman Emperor and “fake news
had allowed Octavian to hack the
republican system once and for
all”.
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66
188 T S M M
Ashleigh Jacobs, African Product Manager for Hootsuite, YOU
KNOW Digital
The evolution of Social Media
Marketing has progressed remarkably
over the last few years, and after
COVID-19, we’re about to see further
pivots in digital evolution. What does
this mean for businesses engaging
in this form of marketing? We break
down some of the facts below.
While the Big 5 of social networks
(Facebook, Instagram, Twitter,
LinkedIn, YouTube) have maintained
majority share in markets in Africa,
there are several other networks
gaining interest. Pinterest, Snapchat,
Twitch, TikTok are just a few that are
catching up. These networks bring
added value to users by focusing on
niche elements, often using short-
form video content as the hook.
On a global scale, video platforms
like Snapchat and TikTok are quite
popular, but what is the landscape in
Kenya?
The below graph compiled from We
Are Social’s 2020 Digital Report,
shows the most used social networks
in Kenya as of the beginning of this
year.
At the top of the list, WhatsApp is the
favourite communication platform in
Kenya, with YouTube and Facebook
close behind. A key development is the
uptake in visual content consumed
from social media users has become
highly popular.
As a marketer- where is the most
impactful place to create awareness
for your brand?
The graph on the next page from
the We Are Social report shows that
ads on social media and television
are ideal for Kenyan markets. Social
ads especially provide a great way for
marketers to advertise their brand
or product via niche targeting and
affordable costs.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
67
From the above findings, it’s
evident that the Big 5 are still the
golden key in social marketing.
With the threat of the new
platforms catching on, how are
these networks pivoting to be
more innovative and own the
market?
Let’s break down some recent
developments from a few
platforms:
Facebook - Enhanced live
streaming features via Facebook
Messengers such as group calling
sessions (similar to Zoom);
Instagram - ‘Instagram Shops’
a new e-commerce feature and
virtual storefront for businesses
where consumers can make
purchase directly from the app;
Twitter - When tweeting, users
can choose who has the ability
to reply.
Along with the above, social
networks are also working on
curbing the spread of fake news
and abuse. Networks have built-in
new options such as red-flagging
users or comments, easier fact-
checking, and limiting the ability
for users to reply. These are all
ways in which social networks
are limiting the spread of
misinformation.
To conclude, what does this mean
for Kenyan marketers?
Before marketing on new
platforms consider where
your target audience is
consuming content the
most, and where they
discover new brands
It is important to keep up
to date on social platforms
changes, as in some cases
there could be monthly
updates to enhance your
marketing efforts
Reporting is key to see if
you’re getting the value you
need from social networks.
Platforms like Hootsuite (a
social media management
tool) aids in the analysis of
your marketing efforts.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
68
189 S M A
Augustine Kihiko, University of KwaZulu-Natal
In Kenya, mobile network coverage
stands at 89%. This presents an
opportunity for technological
advancement through social media
while also posing a challenge in
over-use of social media. Addiction
to social media use comes with
the behavioral traits that may
compare to substance consumption
and addiction like alcoholism
and smoking. Such behavioral
characteristics may include conflict,
relapse, social withdrawal, and mood
swings.
In Kenya, extroverts appear to
use more social media tools for
enhancement, whereas their
introvert counterparts use them
for social compensation. Notably,
any of these addictions in Kenya
need to reach certain levels before
experts consider them pathological
behavior. Social media addiction is
notably visible among Kenyan youth,
especially college and university
students. In 2008, the World Health
Organization (WHO) categorized
video games on social media as a
disorder. In addition, researchers
indicate that internet gambling and
social media addiction have been
gradually increasing.
Social media addiction panders
to two of the most compelling
human psychological instincts that
are exhibitionism and voyeurism.
Research is already proving that the
uncontrolled increase in the use of
social media correlates with a gush
of mental affluence such as anxiety
and depression.
According to a report from the Nation
Media Group, Mr. Fabio Ogachi, a
psychologist at Kenyatta University
in his research, noticed a peculiar
trend in social media use. The report
confirms that people addicted to the
internet had several symptoms of
depression, i.e., pathological internet
users’ exhibit negative consequences
of bad social relations (Lamenager
et al., 2018). Furthermore, they have
psychological disturbances and poor
academic performance.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
69
In his publication, “Relationship
between pathological internet
users and depression,” Mr.
Ogachi argues that 17% of
Kenyan university students have
a severe addiction to the internet
(Waithaka et al., 2018). Moreover,
23% of the participants in his
study were fighting the mental
effects of addiction to the internet
and severe depression condition
(da Silva et al., 2019). These study
findings prove that addiction to
the internet is a significant cause
of mental illness among youths.
Thus, social media becomes the
main culprit in the increased
prevalence of personality and
social disorders. The matter ripe
for discussion now is whether
depression is a cause of increased
use of social media, especially
among the youth.
Chronic addiction to social media
affects our relationships, health,
careers, and studies. More in-
depth discussions and research
ought to focus on whether to
blame social media on the rise
depression among the youths
in Kenya and around the world.
Therefore, we all need to educate
ourselves on how to take control
and lead digitally minimal
lives if we want to have holistic
experiences. We should not live in
fear of missing out but direct our
energy on the proper use of social
media to improve our lives and
economy.
References
1. da Silva, A. C., Vargas, L. S., Moraes, R. C. C., Lucchese, R., Guimarães, R. A.,
& Vera, I. (2019). Prevalence and factors associated with common mental
disorder in rural settlers. SMAD, Revista Electrónica en Salud Mental,
Alcohol y Drogas, 15(1), 23-31.
2. Lemenager, T., Hoffmann, S., Dieter, J., Reinhard, I., Mann, K., & Kiefer, F.
(2018). The links between healthy, problematic, and addicted Internet
use regarding comorbidities and self-concept-related characteristics.
Journal of behavioral addictions, 7(1), 31-43.
3. Waithaka, M., Onyancha, O. B., & Ngulube, P. (2018). Internet use among
university students in Kenya: a case study of the University of Nairobi.
Innovation: journal of appropriate librarianship and information work in
Southern Africa, 2018(57), 45-69.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
70
1810 A P C: S M M
Kevin C. Mudavadi, USIU-Africa
When Canadian media theorist
Marshall McLuhan foresaw a
connected world without any
boundaries, he spoke of the ‘global
village’ in 1960s, that is, a society
interconnected through media
technologies. A platform that afforded
everyone around the world a chance to
communicate and experience issues
around the world from the comfort of
their sofas. These media technologies
such as social media have even seen
the rise of citizen journalism. This has
meant that people are ready to share
information first and fast.
However, this leaves a gap on the
authentic nature of information and
gives rise to questions such as; whom
can we trust? What information is true
or false? What can be done to reduce
spread of misinformation so prevalent
on social media accounts? In a time
of crisis, individuals do rush to friends,
the media, and organizational sites
for information - majority choosing
the media. Social media has served
as a platform that affords individuals
the chance to share information and
open room for discussions.
These social media platforms however,
do not have means to limit spread of
fake news. Many users do not have
time to check if the information is true
or false. As such, they are likely to be
victims of fake news or misinformation.
The Covid-19 pandemic has seen
multiple of conversations on social
media - many of which have been
misinformation. Fake news has a
big role on how individuals interpret
health information. In fact, in this
pandemic, one blogger countered
government information and sparked
a lot of muddle online. Research done
in Kenya has shown that citizens
encounter misinformation and many
a times, they are likely to share it with
their friends or those close to their
networks. As such, there is need to
train the public on media literacy and
ways to verify information online lest
we risk a jumbled society!
1811 T B C A
Kelvin Jonck, MD, YOUKNOW Digital
There are two opposing, yet ironically
complementary, forces at play in the
social data space at the moment.
On the one side, you have the social
analytics and social intelligence
companies such as Brandwatch,
Buzzsumo, Netbase and others
wanting to provide their clients with
richer and more valuable insights
based on analysing social data from
social networks, such as Facebook,
Instagram and Twitter.
On the other side, you have the data
departments of these exact same
social networks.
Leading up to, and after, the
Cambridge Analytica scandal, social
networks have been under a lot
of pressure to reduce the amount
of individual user data which they
make public, or which they make
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
71
accessible to 3rd parties (such
as app developers and the
social intelligence companies.)
However, to allow their partners
to enrich the user and marketer’s
experiences there does need to
be the ability to share some of
that data.
In the world of social media
intelligence providers, it becomes
increasingly valuable to allow
their customers (marketers
and researchers, for example)
to be able to understand what
consumers want through what
they say publicly on social
platforms: their needs, desires,
preferences and grievances. It
helps to be able to segment
those audiences into tangible
groups which can more easily be
addressed. It helps to know that
the Gen Z entrepreneur, from
Soweto, needs better network
signal to build their business. Or
that new mothers, under the age
of 28, in certain urban regions,
prefer same-day delivery over
discounts when doing their online
shopping.
With this in mind, not all social
networks are created equal, or
have the same views on how their
user’s data should be leveraged.
Facebook (and hence Instagram
and WhatsApp) cares more
about leveraging that data to sell
advertising on their platforms.
They don’t make much money off
of the sale of data to 3rd parties,
such as the social listening
companies. Twitter, on the other
hand, does have a robust data
strategy. Being, for the most
part, a public network, Twitter
still provides access to public
conversations on its network for
the purposes of market research,
brand reputation analysis and
other forms of insights. They
do, however, restrict where that
data can be used - such as their
restrictions on working with
governments from countries
deemed to be “not free”.
These changing attitudes
to how social data can and
should be used has led to many
organisations looking elsewhere
for complementary, collective
data; the merger of concepts such
as solicited and unsolicited data.
There is an increasing awareness
that to have a better view of the
consumer, the need to combine
social data, behavioural analytics,
market research data and other
sources in your evaluations and
planning is essential.
Brandwatch, the social listening
giant, for example, realised
this and acquired a market
research, polling technology,
called Qriously. Qriously works by
purchasing programmatic display
ads and presents users with short,
interactive polls - the results
of which are instantaneously
analysed and presented back
to the researcher. This market
analysis can then be overlayed
with social data to understand
what people think when you ask
them a question (solicited), as well
as when you don’t (unsolicited).
There is a distinct difference
between what people will
advertise about themselves
on public social networks, as
opposed to what they’ll admit to
via anonymous survey responses.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
72
For example, via surveys, respondents
may disclose their household
incomes, their credit ratings and
even marital status (single, married,
divorced). On social, some may be less
willing to share those insights, but will
gladly tell you their view on the latest
Marvel movie before you need to ask.
At YOUKNOW, we’ve seen an
increased requirement from our
clients to look at solicited market
research at speed. We recently
partnered with GlobalWebIndex to
provide their unique approach to
understanding digital audiences to
South Africa.
At the end of the day, insightful
human analysis is still required to find
the nuggets of gold in the data. But
it’s become increasingly clear that
one source of truth is not going to
cut it. The winners look at multiple
views of their consumers and are able
to combine that with the knowledge
of their industry to take their
organization to the next level.
Kelvin’s final thought for the industry:
The data will get you 50% there.
Invest in smart people to take you
the rest of the way.
1812 A S M
Immaculate Tallam, SIMElab
Since the dawn of Web 2.0, social
media has significantly matured,
developing specific strategic uses
within society. This growth has
adopted the use of anonymity, which
has created immense benefits for
its users on a personal and societal
level. Though beneficial, conflicting
views remain its continued use going
forward.
Johan Helsingius, a digital pioneer,
stated that anonymity is beneficial as
it gives an outlet for the unreserved
expression of opinions, including
controversial ones. Our society is
conservative, often making it ‘unsafe’
for netizens to make absolute
statements or hold unpopular
opinions. Thus, in our context,
anonymity has been used as a tool to
break out of our conservative shells.
Anonymity has become an invaluable
tool in controlling discourse
surrounding societal issues. Netizens
have been able to find a voice within
online spheres, which has, in many
cases, enabled them to broker
significant political changes. For
instance, the ongoing ‘Black Lives
Matter’ campaign against police
brutality has led to legislative changes
in the United States of America.
Similarly, local campaigns have run in
Kenya, in hopes of initiating changes.
Connected to this is the observed
increase in political participation
caused by the perceived power
wielded by online users to foster
democratic change.
In recent years, blogging and
microblogging alike have influenced
the political participation of previously
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
73
unengaged citizens. Locally, the
Twitter and Facebook platforms
have been used as a political
campaign tool, confirming the
correlation between online politics
and votes cast. Pseudonyms
have served to protect against
unwarranted prejudice. Online
views may, sometimes, be used
against its holders by both
public and private persons.
Significant concerns lie when
expressing views contrary to the
government’s, which may lead to
arrests, prosecution, or non-legal
retribution. Though not wholly
capable, some individuals have
successfully shielded themselves
from government surveillance
through the use of anonymity.
In conclusion, the two conflicting
views arise from the use of
anonymity online. On the one
hand, anonymity is a tool used to
facilitate the freedom of expression,
while on the other hand, it is
also seen as an impediment to
genuinely free speech, with some
stating that convictions should
be made known without having
to hide behind a veil. Whichever
side one agrees with, the benefits
of anonymity, such as advancing
public discussion, protecting
political disputes and furthering
due process, cannot be denied.
1813 S L - W
Kristina Sutton, Senior Account Executive for Brandwatch,
YOUKNOW Digital
Let’s face it - conversations on
social media can be intense.
Protected by the barrier of a
screen, dozens of emotional
discussions are happening daily
about everything from frustrations
with telecoms providers, preferred
delivery services, fast food debates,
insurance, healthcare, retailers and
fashion giants.
Businesses who leverage
social listening - the ability
to search out and aggregate
conversations mentioning a
brand or competitors - have the
upper hand in understanding
consumers’ perceptions of them.
Social-listening gives businesses a
real-time window into sentiment,
reputation and competitive share-
of-voice.
Brands in Africa that keep a close
ear to the social-sphere include
MTN, Multichoice, Vodacom, Tiger
Brands, Samsung, Standard Bank
and major agencies that represent
consumer brands - all with the
end goal to report on marketing
efforts and to achieve relevance
with their customers.
However, in 2020, branded
conversation is just one piece of
the puzzle. Statistics tell us that
96% of online conversation is
unbranded.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
74
Why does that matter, and how
can brands harness the 96%?
When brands zoom out into the
wider industry conversations,
using industry-leading listening
and consumer research tools, like
Brandwatch - amazing things can
happen. We’ve seen our clients pivot
strategies on the fly from these
insights.
TymeBank - South Africa’s first digital
bank - decided not to focus on what
consumers might dislike about their
brand, but instead zoomed out to
beg the question, “What do South
Africans hate about banking in our
country?” The answers helped inform
their marketing strategy for months
to come.
Coca-Cola moved beyond looking
at competitors and focused on a key
factor in their growth and strategy -
Sugar. They answered questions like:
How are consumers talking about
sugar? What is the impact of the
sugar tax? How can we position our
offering with this data?
Tesla, when looking to expand
into a new market, listened for the
conversations around electric cars
to inform, geographically, where the
most interest was concentrated. They
then segmented the data further on
‘What about electric cars resonates
with this market the best’ in order to
inform their go-to-market strategy.
The best businesses are approaching
social listening with a wider lens.
What do all of these businesses
have in common? The technology
they use: Brandwatch Consumer
Research.
Bottom line: We all know predicting
the future is difficult, but research
is less work than guess work.
Social-listening, both branded and
unbranded, can provide answers to
even the biggest consumer questions.
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
75
SIMEL T
Patrick Kanyi Wamuyu is an Associate Professor of
Information Technology at United States International
University-Africa, Nairobi, Kenya. Dr. Wamuyu
earned his Ph.D. degree in Information Systems and
Technology from the University of KwaZulu-Natal,
Durban, South Africa. He completed his postdoctoral
research at the Indian Institute of Information
Technology, Allahabad, India and the Freie Universität,
Berlin, Germany. His research focuses on a broad range
of topics related to Information and Communication
Technologies for Development (ICT4D), Digital Media
in Civic and Political Participation in Developing
Countries, e-business infrastructures, ICT Innovations
and Entrepreneurship, Wireless Sensor Networks and
Databases. He has published in Six of the premier
publishing houses namely: Elsevier, Springer, IEEE,
Wiley-Blackwell, Emerald and Taylor & Francis as well as
in various other Information Systems and Technology
journals. His academic publications include a book,
book chapters, peer reviewed journal articles, and
conference proceedings. He has over twenty years
of experience in the computing and information
technology industry that have taken him from
software development, running his own Information
Technology Enterprise to the academic world. He
has advised many graduate (Masters and Ph.D.) and
undergraduate students. He is Chair, Department of
Computing in the School of Science & Technology at
USIU-Africa.
David Lomoywara works
at SIMElab as a researcher.
Before joining SIMElab,
David worked for two years
as a Graduate Assistant
School of Communication,
Cinematics, and Creative
Arts at USIU-Africa. He is a
registered member of The
Association for Education
in Journalism and Mass
Communication (AEJMC),
and he has presented
conference papers in Kenya
on social media and health
communication. David is also
a reviewer- he was among
reviewers who reviewed
articles for the ICA Health
Communication section for
the conference held in May
2020 in Australia. David
pursued B.A in Journalism
and a Masters of Arts in
Communication Studies
both at USIU-Africa.
Patrick Kanyi Wamuyu, Ph.D.
SIMElab Coordinator
David Lomoywara
The Kenyan Social Media Landscape: Trends and Emerging Narratives, 2020
76
Jacktone Momanyi is currently
pursuing an MSc. in Information
Systems and Technology at USIU-
Africa. He also holds a bachelor’s
degree in Information Systems
and Technology from USIU-Africa.
Momanyi has also covered classes
on database administration, online
marketing (Google digital skills for
Africa) and Web analytics (Google
Analytics). As a Data Scientist at
USIU-Africa’s SIMElab, he specializes
in Social Network Analysis (SNA),
Natural Language Processing (NLP)
and Big Data Analytics. He also serves
as technical assistant and trainer
to both industry and academia for
Brandwatch Consumer Research
and NodeXL. Prior to joining SIMElab,
he worked as business intelligence
intern at USIU-Africa’s Business
Application department where he
was involved in visualizing data and
creating dashboards for managerial
decision making. He also worked
at Child.org, a non-governmental
organization as a data analyst in the
M&E department.
Jackton Momanyi Immaculate Tallam Austin Owuor
Immaculate Tallam is a graduate
student at USIU pursuing an MSc.
Information Systems Technology
and serves as a research assistant at
SIMElab, utilizing her competencies to
gravitate towards impactful research.
Her role is to extract data, diagnose,
critique, and catalog data to derive
significant insights. Immaculate’s role
in the data science field (Afterwork
Data Science Fellowship) is to derive
meaningful acumen from data and
conducts weekly trainings on Social
Media Analytics.
Austin Owuor is a researcher at SIMElab and is a
graduate student pursuing MSc. Information Systems
Technology at USIU-Africa. Austin is a Certified |Cisco
Network Analyst with expertise also in programming
and big data. He is passionate about analysis of the
social media networks and interpretation of the
advanced network metrics. He also has an interest
in human-computer interaction and knowledge
management. He has participated and presented
papers in both local and international conferences,
including SIMElab’s annual International Symposium
on Social Media and African Higher Education
Research Institute (AHERI) conference.
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by demographics and culture on social media, Journal of Information
Technology & Politics, 17(1),1-11,
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